diff options
| -rw-r--r-- | scraper/datasets/citations-1.csv | 77 | ||||
| -rw-r--r-- | scraper/datasets/citations-2.csv | 89 | ||||
| -rw-r--r-- | scraper/datasets/citations-20181031.csv (renamed from scraper/datasets/citations-2018310.csv) | 0 | ||||
| -rw-r--r-- | scraper/datasets/citations-20181207.csv | 437 | ||||
| -rw-r--r-- | scraper/datasets/citations-3.csv | 51 | ||||
| l--------- | scraper/datasets/citations.csv | 2 | ||||
| -rw-r--r-- | scraper/s2-papers.py | 18 | ||||
| -rw-r--r-- | scraper/s2-search.py | 6 | ||||
| -rw-r--r-- | scraper/s2.py | 21 |
9 files changed, 463 insertions, 238 deletions
diff --git a/scraper/datasets/citations-1.csv b/scraper/datasets/citations-1.csv deleted file mode 100644 index f9400fcd..00000000 --- a/scraper/datasets/citations-1.csv +++ /dev/null @@ -1,77 +0,0 @@ -Database Name,Title,Journal/Pub/Conference,Year,Pages,Volume,Author1,Author2,Author3,Author4,Author5,Author 6,PDF,Priority,URL,bibtex_reference_only,notes
-PIE,"The CMU Pose, Illumination, and Expression Database",IEEE Transactions on Pattern Analysis and Machine Intelligence,Dec 2003,"25, No. 12",,T. Sim,S. Baker,M. Bsat,,,,,,http://www.cs.cmu.edu/~simonb/pie_db/pami.pdf,,
-YouTubeFaces,Face Recognition in Unconstrained Videos with Matched Background Similarity,IEEE Conf. on Computer Vision and Pattern Recognition (CVPR),2011,,,Lior Wolf,Tal Hassner,Itay Maoz,,,,,,,,
-Names and Faces,Who's in the Picture ,NIPS,2004,,,Tamara L. Berg,Alexander C. Berg,Jaety Edwards,David A. Forsyth,,,,2,http://www.cs.berkeley.edu/%7Eaberg/papers/berg_whos_in_the_picture.pdf,,
-RaFD ,Presentation and validation of the Radboud Faces Database,Cognition & Emotion,2010,1377-1388,24.8,"Langner, O.","Dotsch, R."," Bijlstra, G.","Wigboldus, D.H.J.","Hawk, S.T.","van Knippenberg, A.",,,http://dx.doi.org/10.1080/02699930903485076,DOI: 10.1080/02699930903485076,
-MIFS,Spoofing Faces Using Makeup: An Investigative Study,"Proc. of 3rd IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), (New Delhi, India)",2017,,,C. Chen,A. Dantcheva,T. Swearingen,A. Ross,,,,,http://www.cse.msu.edu/~rossarun/pubs/ChenFaceMakeupSpoof_ISBA2017.pdf,,
-MegaFace 2,The MegaFace Benchmark: 1 Million Faces for Recognition at Scale,IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016,,,"Kemelmacher-Shlizerman, Ira","Seitz, Steven M","Miller, Daniel","Brossard, Evan",,,,If you're using or participating in Challenge 1 please cite:,http://megaface.cs.washington.edu/KemelmacherMegaFaceCVPR16.pdf,"@inproceedings{kemelmacher2016megaface, -title={The megaface benchmark: 1 million faces for recognition at scale}, -author={Kemelmacher-Shlizerman, Ira and Seitz, Steven M and Miller, Daniel and Brossard, Evan}, -booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, -pages={4873--4882}, -year={2016} -}",
-CMDP,Distance Estimation of an Unknown Person from a Portrait ,"ECCV 2014, Zurich, Switzerland",2014,,,X. P. Burgos-Artizzu,M.R. Ronchi,P. Perona,,,,,,http://www.vision.caltech.edu/~mronchi/papers/ECCV14_FaceDistancePortrait_PAPER.pdf,"@incollection{perona2014PortraitDistanceEstimation, - title={Distance Estimation of an Unknown Person from a Portrait}, - author={Xavier P. Burgos-Artizzu, Matteo Ruggero Ronchi and Pietro Perona}, - booktitle={Computer Vision--ECCV 2014}, - pages={313--327}, - year={2014}, - publisher={Springer} -} -",
-MORPH non-commercial,MORPH: A Longitudinal Image Database of Normal Adult Age-Progression,"IEEE 7th International Conference on Automatic Face and Gesture Recognition, Southampton, UK",2006,341-345,,Karl Ricanek Jr,Tamirat Tesafaye,,,,,,,,,
-CK+,The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression,"Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), San Francisco, USA",2010,94-101,,"Ambadar, Z.","Cohn, J.F.","Kanade, T.","Lucey, P.","Matthews, I.A.","Saragih, J.M.",,,http://ieeexplore.ieee.org/document/5543262/,"@article{Lucey2010TheEC, - title={The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression}, - author={Patrick Lucey and Jeffrey F. Cohn and Takeo Kanade and Jason M. Saragih and Zara Ambadar and Iain A. Matthews}, - journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops}, - year={2010}, - pages={94-101} -}",
-LFWP,Localizing Parts of Faces Using a Consensus of Exemplars,Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2011,,,Peter N. Belhumeur,"David W. Jacobs,",David J. Kriegman,Neeraj Kumar,,,,,http://neerajkumar.org/projects/face-parts/base/papers/nk_cvpr2011_faceparts.pdf,,
-Adience,Age and Gender Estimation of Unfiltered Faces,"Transactions on Information Forensics and Security (IEEE-TIFS), special issue on Facial Biometrics in the Wild",2014,2170 - 2179,9,Eran Eidinger,Roee Enbar, Tal Hassner,,,,,,http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf,,
-300-W,300 Faces in-the-Wild Challenge: The first facial landmark localization Challenge,"Proceedings of IEEE Int’l Conf. on Computer Vision (ICCV-W), 300 Faces in-the-Wild Challenge (300-W). Sydney, Australia",2013,,,C. Sagonas,G. Tzimiropoulos,S. Zafeiriou,M. Pantic,,,,2,,,
-AFW,"Face detection, pose estimation and landmark localization in the wild","Computer Vision and Pattern Recognition (CVPR) Providence, Rhode Island,",2012,,,X. Zhu,D. Ramanan,,,,,,,http://www.ics.uci.edu/~xzhu/paper/face-cvpr12.pdf,,
-MsCeleb,MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,European Conference on Computer Vision,2016,,,"Guo, Yandong","Zhang, Lei","Hu, Yuxiao","He, Xiaodong","Gao, Jianfeng",,,,https://www.microsoft.com/en-us/research/wp-content/uploads/2016/08/MSCeleb-1M-a.pdf,"@INPROCEEDINGS { guo2016msceleb, - author = {Guo, Yandong and Zhang, Lei and Hu, Yuxiao and He, Xiaodong and Gao, Jianfeng}, - title = {M{S}-{C}eleb-1{M}: A Dataset and Benchmark for Large Scale Face Recognition}, - booktitle = {European Conference on Computer Vision}, - year = {2016}, - organization={Springer}}",
-LAG,Large Age-Gap Face Verification by Feature Injection in Deep Networks,Pattern Recognition Letters,2017,36-42,90,Simone Bianco,,,,,,bianco2017large-age.pdf,,http://www.ivl.disco.unimib.it/activities/large-age-gap-face-verification/,,
-IMDB,DEX: Deep EXpectation of apparent age from a single image,IEEE International Conference on Computer Vision Workshops (ICCVW),Dec 2015,,,Rasmus Rothe,Radu Timofte,Luc Van Gool,,,,,2,,"@InProceedings{Rothe-ICCVW-2015, - author = {Rasmus Rothe and Radu Timofte and Luc Van Gool}, - title = {DEX: Deep EXpectation of apparent age from a single image}, - booktitle = {IEEE International Conference on Computer Vision Workshops (ICCVW)}, - year = {2015}, - month = {December}, -}",
-IMDB,Deep expectation of real and apparent age from a single image without facial landmarks,International Journal of Computer Vision (IJCV),Jul 2016,,,Rasmus Rothe,Radu Timofte,Luc Van Gool,,,,,1,,"@article{Rothe-IJCV-2016, - author = {Rasmus Rothe and Radu Timofte and Luc Van Gool}, - title = {Deep expectation of real and apparent age from a single image without facial landmarks}, - journal = {International Journal of Computer Vision (IJCV)}, - year = {2016}, - month = {July}, -}",
-UMD,UMDFaces: An Annotated Face Dataset for Training Deep Networks,Arxiv preprint,2016,,,Ankan Bansal,Anirudh Nanduri,Carlos D Castillo,Rajeev Ranjan,Rama Chellappa,,,1,https://arxiv.org/abs/1611.01484v2,"@article{bansal2016umdfaces, - title={UMDFaces: An Annotated Face Dataset for Training Deep Networks}, - author={Bansal, Ankan and Nanduri, Anirudh and Castillo, Carlos D and Ranjan, Rajeev and Chellappa, Rama} - journal={arXiv preprint arXiv:1611.01484v2}, - year={2016} - }",
-LFW,Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments.,"University of Massachusetts, Amherst, Technical Report ",2007,07-49,,Gary B. Huang,Manu Ramesh,Tamara Berg,Erik Learned-Miller,,,,,http://vis-www.cs.umass.edu/lfw/lfw.pdf,,various citaton depending on various datasets provided. Citation used here was first one published in 2007
-CelebA,From Facial Parts Responses to Face Detection: A Deep Learning Approach,"in IEEE International Conference on Computer Vision (ICCV),",2015,,,S. Yang,P. Luo,C. C. Loy,X. Tang,,,,,https://arxiv.org/abs/1509.06451,"The following paper employed CelebA for face detection. (linked on the project website) @inproceedings{liu2015faceattributes, - author = {Ziwei Liu and Ping Luo and Xiaogang Wang and Xiaoou Tang}, - title = {Deep Learning Face Attributes in the Wild}, - booktitle = {Proceedings of International Conference on Computer Vision (ICCV)}, - month = December, - year = {2015} -}",
-UMD,The Do's and Don'ts for CNN-based Face Verification,Arxiv preprint,2017,,,Ankan Bansal,Carlos Castillo,"Rajeev Ranjan,",Rama Chellappa,,,,2,https://arxiv.org/abs/1705.07426,"@article{bansal2017dosanddonts, - title = {The Do's and Don'ts for CNN-based Face Verification}, - author = {Bansal, Ankan and Castillo, Carlos and Ranjan, Rajeev and Chellappa, Rama}, - journal = {arXiv preprint arXiv:1705.07426}, - year = {2017} - }",
-Yale Face Database B,From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose,PAMI,2001,,,Athinodoros Georghiades,Peter Belhumeur,David Kriegman,,,,,,,,
-CAISA Webface,Learning Face Representation from Scratch,arXiv preprint arXiv:1411.7923.,2014,,,Dong Yi,Zhen Lei, Shengcai Liao,Stan Z. Li,,,,,https://arxiv.org/abs/1411.7923,,
diff --git a/scraper/datasets/citations-2.csv b/scraper/datasets/citations-2.csv deleted file mode 100644 index ec11b2d0..00000000 --- a/scraper/datasets/citations-2.csv +++ /dev/null @@ -1,89 +0,0 @@ -Database Name,Title,Journal/Pub/Conference,Year,Pages,Volume,Author1,Author2,Author3,Author4,Author5,Author 6,PDF,Priority,URL,bibtex_reference_only,notes
-COFW,Robust face landmark estimation under occlusion ,"ICCV 2013, Sydney, Australia",2013,,,X. P. Burgos-Artizzu,P. Perona,P. Dollár,,,,,,http://www.vision.caltech.edu/%7Expburgos/papers/ICCV13%20Burgos-Artizzu.pdf,,
-Names and Faces,Names and Faces ,U.C. Berkeley Technical Report,Jan. 2007,,,Tamara L. Berg,Alexander C. Berg,Jaety Edwards,Michael Maire,Ryan White,"Yee Whye Teh, Erik Learned-Miller, David A. Forsyth",,1,http://www.cs.berkeley.edu/%7Eaberg/papers/journal_berg.pdf,,
-FaceTracer,FaceTracer: A Search Engine for Large Collections of Images with Faces,European Conference on Computer Vision (ECCV),2008,340-353,,N. Kumar,P. N. Belhumeur,S. K. Nayar,,,,,1,http://www1.cs.columbia.edu/CAVE/publications/pdfs/Kumar_ECCV08.pdf,,
-MIW,Automatic Facial Makeup Detection with Application in Face Recognition,"Proc. of 6th IAPR International Conference on Biometrics (ICB), (Madrid, Spain)",2013,,,C. Chen,A. Dantcheva,A. Ross,,,,,,https://www.cse.msu.edu/~rossarun/pubs/ChenMakeupDetection_ICB2013.pdf,,
-SVW,Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis,"Proc. International Conference on Automatic Face and Gesture Recognition (FG 2015), Ljubljana, Slovenia",2015,,,Seyed Morteza Safdarnejad, Xiaoming Liu, Lalita Udpa, Brooks Andrus,"John Wood,",Dean Craven,,,http://cvlab.cse.msu.edu/pdfs/Morteza_FG2015.pdf," @inproceedings{ sports-videos-in-the-wild-svw-a-video-dataset-for-sports-analysis, - author = { Seyed Morteza Safdarnejad and Xiaoming Liu and Lalita Udpa and Brooks Andrus and John Wood and Dean Craven }, - title = { Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis }, - booktitle = { Proc. International Conference on Automatic Face and Gesture Recognition }, - address = { Ljubljana, Slovenia }, - month = { May }, - year = { 2015 }, -} ",
-LFW-a,,,,,,,,,,,,,,,Comply with any instructions specified for the original LFW data set,
-Helen,Interactive Facial Feature Localization,ECCV,2012,,,Vuong Le,Jonathan Brandt,Zhe Lin,Lubomir Boudev,Thomas S. Huang,,,,http://www.ifp.illinois.edu/~vuongle2/helen/eccv2012_helen_final.pdf,,
-Caltech 10K Web Faces,Pruning Training Sets for Learning of Object Categories,Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2005,,,Anelia Angelova,Yaser Abu-Mostafa,Pietro Perona,,,,,,http://www.vision.caltech.edu/anelia/DataPruning/Angelova05DataPruning.pdf,This is a paper using the dataset (linked on the project website),
-FaceTracer,Face Swapping: Automatically Replacing Faces in Photographs,ACM Trans. on Graphics (also Proc. of ACM SIGGRAPH),2008,,,D. Bitouk,N. Kumar,S. Dhillon,P.N. Belhumeur,S. K. Nayar,,,2,http://www1.cs.columbia.edu/CAVE/publications/pdfs/Bitouk_SIGGRAPH08.pdf,,
-HRT Transgender Database,Is the Eye Region More Reliable Than the Face? A Preliminary Study of Face-based Recognition on a Transgender Dataset,"In Proc. of IEEE Intl. Conf. on Biometrics: Theory, Applications, and Systems",2013,,,Gayathri Mahalingam,Karl Ricanek Jr.,,,,,,,https://pdfs.semanticscholar.org/b066/733d533250f4ddafd22c12456def7fa24f4c.pdf,,
-MUCT,The MUCT Landmarked Face Database,Pattern Recognition Association of South Africa,2010,,,,S. Milborrow,J. Morkel,F. Nicolls,,,,,http://www.milbo.org/muct/The-MUCT-Landmarked-Face-Database.pdf,"@article{Milborrow10, - author={S. Milborrow and J. Morkel and F. Nicolls}, - title={{The MUCT Landmarked Face Database}}, - journal={Pattern Recognition Association of South Africa}, - year=2010, - note={\url{http://www.milbo.org/muct}} -}",
-AFLW,"Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization",,,,,Martin Koestinger,Paul Wohlhart,Peter M. Roth,Horst Bischof,,,,,https://files.icg.tugraz.at/seafhttp/files/d18813db-78c3-46a9-8614-bc0c8d428114/koestinger_befit_11.pdf,"@INPROCEEDINGS{koestinger11a, - author = {Martin Koestinger, Paul Wohlhart, Peter M. Roth and Horst Bischof}, - title = {{Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization}}, - booktitle = {{Proc. First IEEE International Workshop on Benchmarking Facial Image Analysis Technologies}}, - year = {2011} -} ",
-PIPA,Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues,arXiv:1501.05703 [cs.CV],2015,,,Ning Zhang, Manohar Paluri,Yaniv Taigman,Rob Fergus,Lubomir Bourdev,,,,https://arxiv.org/pdf/1501.05703.pdf,"@inproceedings{piper, - Author = {Ning Zhang and Manohar Paluri and Yaniv Taigman and Rob Fergus and Lubomir Bourdev}, - Title = {Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues}, - Eprint = {arXiv:1501.05703}, - Year = {2015}}",
-UCF101,UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild,CRCV-TR-12-01,2012,,,"Soomro, K.","Roshan Zamir, A.","Shah, M.",,,,,2,,"@inproceedings{UCF101, - author = {Soomro, K. and Roshan Zamir, A. and Shah, M.}, - booktitle = {CRCV-TR-12-01}, - title = {{UCF101}: A Dataset of 101 Human Actions Classes From - Videos in The Wild}, - year = {2012}}",
-YMU,Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?,"Proc. of 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Washington DC, USA)",2012,,,A. Dantcheva,C. Chen,A. Ross,,,,,1,https://www.cse.msu.edu/~rossarun/pubs/DantchevaChenRossFaceCosmetics_BTAS2012.pdf,,
-FDDB,FDDB: A Benchmark for Face Detection in Unconstrained Settings,"Technical Report UM-CS-2010-009, Dept. of Computer Science, University of Massachusetts",2010,,,Vidit Jain,Erik Learned-Mille,,,,,,,http://vis-www.cs.umass.edu/fddb/fddb.pdf,"@TechReport{fddbTech, - author = {Vidit Jain and Erik Learned-Miller}, - title = {FDDB: A Benchmark for Face Detection in Unconstrained Settings}, - institution = {University of Massachusetts, Amherst}, - year = {2010}, - number = {UM-CS-2010-009} - }",
-Hipsterwars,Hipster Wars: Discovering Elements of Fashion Styles.,In European Conference on Computer Vision,2014,,,M. Hadi Kiapour,Kota Yamaguchi,Alexander C. Berg,Tamara L. Berg,,,,,http://tamaraberg.com/papers/hipster_eccv14.pdf,"@inproceedings{ - HipsterWarsECCV14, - title = {Hipster Wars: Discovering Elements of Fashion Styles} - author = {M. Hadi Kiapour, Kota Yamaguchi, Alexander C. Berg, Tamara L. Berg}, - booktitle={European Conference on Computer Vision}, - year = {2014} - }",
-LAG,Large Age-Gap Face Verification by Feature Injection in Deep Networks,In Pattern Recognition Letters,2017,36-42,90,Simone Bianco,,,,,,,,http://www.ivl.disco.unimib.it/download/bianco2017large-age.pdf,,
-CMDP,Distance Estimation of an Unknown Person from a Portrait,ECCV 2014,2014,,,X. P. Burgos-Artizzu,M.R. Ronchi,P. Perona,,,,,,,,
-Columbia Gaze Data Set,Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction,ACM Symposium on User Interface Software and Technology (UIST),2013,271-280,,B.A. Smith,Q. Yin,S.K. Feiner,S.K. Nayar,,,,,http://www.cs.columbia.edu/~brian/publications/gaze_locking.html,,
-IJB-A,"Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A -",Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2015,1931-1939,07-12-June-2015,"Klare, B. F.","Klein, B.","Taborsky, E.","Blanton, A.","Cheney, J.","Allen, K., ... Jain, A. K.",,,http://ieeexplore.ieee.org/document/7298803/,"DOI: 10.1109/CVPR.2015.7298803 @inbook{882e95bdca414797b4a8e2bfcb5b1fa4, -title = ""Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A"", -abstract = ""Rapid progress in unconstrained face recognition has resulted in a saturation in recognition accuracy for current benchmark datasets. While important for early progress, a chief limitation in most benchmark datasets is the use of a commodity face detector to select face imagery. The implication of this strategy is restricted variations in face pose and other confounding factors. This paper introduces the IARPA Janus Benchmark A (IJB-A), a publicly available media in the wild dataset containing 500 subjects with manually localized face images. Key features of the IJB-A dataset are: (i) full pose variation, (ii) joint use for face recognition and face detection benchmarking, (iii) a mix of images and videos, (iv) wider geographic variation of subjects, (v) protocols supporting both open-set identification (1:N search) and verification (1:1 comparison), (vi) an optional protocol that allows modeling of gallery subjects, and (vii) ground truth eye and nose locations. The dataset has been developed using 1,501,267 million crowd sourced annotations. Baseline accuracies for both face detection and face recognition from commercial and open source algorithms demonstrate the challenge offered by this new unconstrained benchmark."", -author = ""Klare, {Brendan F.} and Ben Klein and Emma Taborsky and Austin Blanton and Jordan Cheney and Kristen Allen and Patrick Grother and Alan Mah and Mark Burge and Jain, {Anil K.}"", -year = ""2015"", -month = ""10"", -doi = ""10.1109/CVPR.2015.7298803"", -isbn = ""9781467369640"", -volume = ""07-12-June-2015"", -pages = ""1931--1939"", -booktitle = ""Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition"", -publisher = ""IEEE Computer Society"", - -} -",
-AgeDB,"AgeDB: the first manually collected, in-the-wild age database",Proceedings of IEEE Int’l Conf. on Computer Vision and Pattern Recognition (CVPR-W 2017,2017,,,S. Moschoglou,A. Papaioannou,C. Sagonas,J. Deng,I. Kotsia, S. Zafeiriou,,,http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Moschoglou_AgeDB_The_First_CVPR_2017_paper.pdf,"@inproceedings{AgeDB, - author = {S. Moschoglou and A. Papaioannou and C. Sagonas and J. Deng and I. Kotsia and S. Zafeiriou}, - address = {Honolulu, Hawaii}, - booktitle = {Proceedings of IEEE Int’l Conf. on Computer Vision and Pattern Recognition (CVPR-W 2017)}, - month = {June}, - title = {AgeDB: the first manually collected, in-the-wild age database}, - year = {2017}, -}",
-WIDER FACE,WIDER FACE: A Face Detection Benchmark,IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016,,,"Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou",,,,,,,,,"@inproceedings{yang2016wider, - Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou}, - Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, - Title = {WIDER FACE: A Face Detection Benchmark}, - Year = {2016}}",
diff --git a/scraper/datasets/citations-2018310.csv b/scraper/datasets/citations-20181031.csv index 68a3ae3e..68a3ae3e 100644 --- a/scraper/datasets/citations-2018310.csv +++ b/scraper/datasets/citations-20181031.csv diff --git a/scraper/datasets/citations-20181207.csv b/scraper/datasets/citations-20181207.csv new file mode 100644 index 00000000..a5167478 --- /dev/null +++ b/scraper/datasets/citations-20181207.csv @@ -0,0 +1,437 @@ +key,name,title,,,,Comments,,,,publication,day,month,year,pages,vol,author1,author2,author3,author4,author5,author6,funding1,funding2,funding3,funding4,priority,notes,pdf_filename,url,bibtex_copy
+10k_US_adult_faces,10K US Adult Faces,The intrinsic memorability of face images,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+3d_rma,3D-RMA,Automatic 3D Face Authentication,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+3dddb_unconstrained,3D Dynamic,A 3D Dynamic Database for Unconstrained Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+3dpes,3DPeS,3DPes: 3D People Dataset for Surveillance and Forensics,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+4dfab,4DFAB,4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+50_people_one_question,50 People One Question,Merging Pose Estimates Across Space and Time,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+a_pascal_yahoo,aPascal,Describing Objects by their Attributes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+aberdeen ,Aberdeen,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+adience,Adience,Age and Gender Estimation of Unfiltered Faces,,,,,,,,"Transactions on Information Forensics and Security (IEEE-TIFS), special issue on Facial Biometrics in the Wild",,,2014,2170 - 2179,9,Eran Eidinger,Roee Enbar, Tal Hassner,,,,,,,,,,,http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf,
+afad,AFAD,Ordinal Regression with a Multiple Output CNN for Age Estimation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+afew_va,AFEW-VA,"AFEW-VA database for valence and arousal estimation in-the-wild +",,,,"both paper refer to database. ""Collecting..."" describes how the database was created but the statistics we use are in ""afew-va..."". ",,,,IEEE MultiMedia,,,2012,pp. 34-41,"vol. 19, no. 3",,,,,,,,,,,,,"afew-va.pdf +Dhall_Goecke_Lucey_Gedeon_M_2012.pdf",,
+afew_va,AFEW-VA,"Collecting Large, Richly Annotated Facial-Expression Databases from Movies",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+affectnet,AffectNet,"AffectNet: A New Database for Facial Expression, Valence, and Arousal Computation in the Wild",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+aflw,AFLW,"Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization",,,,,,,,,,,,,,Martin Koestinger,Paul Wohlhart,Peter M. Roth,Horst Bischof,,,,,,,,,koestinger_befit_11.pdf,https://files.icg.tugraz.at/seafhttp/files/d18813db-78c3-46a9-8614-bc0c8d428114/koestinger_befit_11.pdf,"@INPROCEEDINGS{koestinger11a, + author = {Martin Koestinger, Paul Wohlhart, Peter M. Roth and Horst Bischof}, + title = {{Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization}}, + booktitle = {{Proc. First IEEE International Workshop on Benchmarking Facial Image Analysis Technologies}}, + year = {2011} +} "
+afw,AFW,"Face detection, pose estimation and landmark localization in the wild",,,,no paper,,,,"Computer Vision and Pattern Recognition (CVPR) Providence, Rhode Island,",,,2012,,,X. Zhu,D. Ramanan,,,,,,,,,,,,http://www.ics.uci.edu/~xzhu/paper/face-cvpr12.pdf,
+agedb,AgeDB,"AgeDB: the first manually collected, in-the-wild age database",,,,,,,,Proceedings of IEEE Int’l Conf. on Computer Vision and Pattern Recognition (CVPR-W 2017,,,2017,,,S. Moschoglou,A. Papaioannou,C. Sagonas,J. Deng,I. Kotsia, S. Zafeiriou,,,,,,,agedb.pdf,http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Moschoglou_AgeDB_The_First_CVPR_2017_paper.pdf,"@inproceedings{AgeDB, + author = {S. Moschoglou and A. Papaioannou and C. Sagonas and J. Deng and I. Kotsia and S. Zafeiriou}, + address = {Honolulu, Hawaii}, + booktitle = {Proceedings of IEEE Int’l Conf. on Computer Vision and Pattern Recognition (CVPR-W 2017)}, + month = {June}, + title = {AgeDB: the first manually collected, in-the-wild age database}, + year = {2017}, +}"
+alert_airport,ALERT Airport,"A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+am_fed,AM-FED,Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+apis,APiS1.0,Pedestrian Attribute Classification in Surveillance: Database and Evaluation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ar_facedb,AR Face,The AR Face Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+awe_ears,AWE Ears,Ear Recognition: More Than a Survey,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+b3d_ac,B3D(AC),A 3-D Audio-Visual Corpus of Affective Communication,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bbc_pose,BBC Pose,Automatic and Efficient Human Pose Estimation for Sign Language Videos ,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+berkeley_pose,BPAD,Describing People: A Poselet-Based Approach to Attribute Classification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bfm,BFM,A 3D Face Model for Pose and Illumination Invariant Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bio_id,BioID Face,Robust Face Detection Using the Hausdorff Distance,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bjut_3d,BJUT-3D,The BJUT-3D Large-Scale Chinese Face Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bosphorus,The Bosphorus,Bosphorus Database for 3D Face Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bp4d_plus,BP4D+,Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bp4d_spontanous,BP4D-Spontanous,A high resolution spontaneous 3D dynamic facial expression database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+brainwash,Brainwash,Brainwash dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+bu_3dfe,BU-3DFE,A 3D Facial Expression Database For Facial Behavior Research,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+buhmap_db,BUHMAP-DB ,Facial Feature Tracking and Expression Recognition for Sign Language,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cafe,CAFE,The Child Affective Facial Expression (CAFE) Set: Validity and reliability from untrained adults,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+caltech_10k_web_faces,Caltech 10K Web Faces,Pruning Training Sets for Learning of Object Categories,,,,This is a paper using the dataset (linked on the project website),,,,Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),,,2005,,,Anelia Angelova,Yaser Abu-Mostafa,Pietro Perona,,,,,,,,,,Angelova05DataPruning.pdf,http://www.vision.caltech.edu/anelia/DataPruning/Angelova05DataPruning.pdf,
+caltech_faces,Caltech Faces,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+caltech_pedestrians,Caltech Pedestrians,Pedestrian Detection: A Benchmark,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+caltech_pedestrians,Caltech Pedestrians,Pedestrian Detection: An Evaluation of the State of the Art,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+camel,CAMEL,CAMEL Dataset for Visual and Thermal Infrared Multiple Object Detection and Tracking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cas_peal,CAS-PEAL,The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations ,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+casablanca,Casablanca,Context-aware {CNNs} for person head detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+casia_webface,CASIA Webface,Learning Face Representation from Scratch,,,,,,,,arXiv preprint arXiv:1411.7923.,,,2014,,,Dong Yi,Zhen Lei, Shengcai Liao,Stan Z. Li,,,,,,,,,1411.7923.pdf,https://arxiv.org/abs/1411.7923,
+caviar4reid,CAVIAR4REID,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+celeba,CelebA,Deep Learning Face Attributes in the Wild,,,,,,,,"in IEEE International Conference on Computer Vision (ICCV),",,,2015,,,S. Yang,P. Luo,C. C. Loy,X. Tang,,,,,,,,,Liu_Deep_Learning_Face_ICCV_2015_paper.pdf,https://arxiv.org/abs/1509.06451,"@inproceedings{liu2015faceattributes,
author = {Ziwei Liu and Ping Luo and Xiaogang Wang and Xiaoou Tang},
title = {Deep Learning Face Attributes in the Wild},
booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
month = December,
year = {2015}
}"
+celeba_plus,CelebFaces+,"Deep Learning Face Representation from Predicting 10,000 Classes",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cfd,CFD,The Chicago face database: A free stimulus set of faces and norming data,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+chalearn,ChaLearn,ChaLearn Looking at People: A Review of Events and Resources,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+chokepoint,ChokePoint,Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition ,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cityscapes,Cityscapes,The Cityscapes Dataset for Semantic Urban Scene Understanding,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cityscapes,Cityscapes,The Cityscapes Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+clothing_co_parsing,CCP,Clothing Co-Parsing by Joint Image Segmentation and Labeling,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cmdp,CMDP,Distance Estimation of an Unknown Person from a Portrait,,,,,,,,ECCV 2014,,,2014,,,X. P. Burgos-Artizzu,M.R. Ronchi,P. Perona,,,,,,,,,,ECCV14_FaceDistancePortrait_PAPER.pdf,http://www.vision.caltech.edu/~mronchi/papers/ECCV14_FaceDistancePortrait_PAPER.pdf,"@incollection{perona2014PortraitDistanceEstimation, + title={Distance Estimation of an Unknown Person from a Portrait}, + author={Xavier P. Burgos-Artizzu, Matteo Ruggero Ronchi and Pietro Perona}, + booktitle={Computer Vision--ECCV 2014}, + pages={313--327}, + year={2014}, + publisher={Springer} +}"
+cmu_pie,CMU PIE,"The CMU Pose, Illumination, and Expression Database",,,,,,,,IEEE Transactions on Pattern Analysis and Machine Intelligence,,12,2003,"25, No. 12",,T. Sim,S. Baker,M. Bsat,,,,,,,,,,,http://www.cs.cmu.edu/~simonb/pie_db/pami.pdf,
+coco,COCO,Microsoft COCO: Common Objects in Context,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+coco_action,COCO-a,Describing Common Human Visual Actions in Images,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+coco_qa,COCO QA,Exploring Models and Data for Image Question Answering,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cofw,COFW,Robust face landmark estimation under occlusion,,,,Paper for RCPR method includes creation of COFW dataset,,,,"ICCV 2013, Sydney, Australia",,,2013,,,X. P. Burgos-Artizzu,P. Perona,P. Dollár,,,,,,,,,,ICCV13 Burgos-Artizzu.pdf,http://www.vision.caltech.edu/%7Expburgos/papers/ICCV13%20Burgos-Artizzu.pdf,
+cohn_kanade,CK,Comprehensive Database for Facial Expression Analysis,,,,,,,,"Proceedings of the Fourth IEEE International Conferenc +e on Automatic Face and Gesture Recognition +(FG'00) +",,,2000,484-490,,"Kanade, T.","Cohn, J. F.","Tian, Y.",,,,,,,,,,download.pdf,http://www.pitt.edu/~jeffcohn/biblio/Cohn-Kanade_Database.pdf,
+cohn_kanade_plus,CK+,The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression,,,,,,,,"Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), San Francisco, USA",,,2010,94-101,,"Ambadar, Z.","Cohn, J.F.","Kanade, T.","Lucey, P.","Matthews, I.A.","Saragih, J.M.",,,,,,,paper.pdf,https://ieeexplore.ieee.org/document/5543262,"@article{Lucey2010TheEC, + title={The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression}, + author={Patrick Lucey and Jeffrey F. Cohn and Takeo Kanade and Jason M. Saragih and Zara Ambadar and Iain A. Matthews}, + journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops}, + year={2010}, + pages={94-101} +}"
+columbia_gaze,Columbia Gaze,Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction,,,,,,,,ACM Symposium on User Interface Software and Technology (UIST),,,2013,271-280,,B.A. Smith,Q. Yin,S.K. Feiner,S.K. Nayar,,,,,,,,,p271-smith.pdf,http://www.cs.columbia.edu/~brian/publications/gaze_locking.html,
+complex_activities,Ongoing Complex Activities,Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cuhk01,CUHK01,Human Reidentification with Transferred Metric Learning,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cuhk02,CUHK02,Locally Aligned Feature Transforms across Views,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cuhk03,CUHK03,DeepReID: Deep Filter Pairing Neural Network for Person Re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+cvc_01_barcelona,CVC-01,Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+czech_news_agency,UFI,Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+d3dfacs,D3DFACS,A FACS Valid 3D Dynamic Action Unit database with Applications to 3D Dynamic Morphable Facial Modelling,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+dartmouth_children,Dartmouth Children,The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+data_61,Data61 Pedestrian,A Multi-Modal Graphical Model for Scene Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+deep_fashion,DeepFashion,DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+deep_fashion,DeepFashion,Fashion Landmark Detection in the Wild,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+disfa,DISFA,DISFA: A Spontaneous Facial Action Intensity Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+distance_nighttime,Long Distance Heterogeneous Face,Nighttime Face Recognition at Long Distance: Cross-distance and Cross-spectral Matching,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+duke_mtmc,Duke MTMC,"Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+emotio_net,EmotioNet Database,"EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+eth_andreas_ess,ETHZ Pedestrian,Depth and Appearance for Mobile Scene Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+europersons,EuroCity Persons,The EuroCity Persons Dataset: A Novel Benchmark for Object Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+expw,ExpW,Learning Social Relation Traits from Face Images,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+expw,ExpW,From Facial Expression Recognition to Interpersonal Relation Prediction,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+face_research_lab,Face Research Lab London,Face Research Lab London Set. figshare,,,,No paper (not even on internet?),,,,,,,2017,,,"DeBruine, Lisa","Jones, Benedict",,,,,,,,,,,,https://doi.org/10.6084/m9.figshare.5047666.v3,
+face_scrub,FaceScrub,A data-driven approach to cleaning large face datasets,,,,,,,,Proc. IEEE International Conference on Image Processing (ICIP),,,2014,,,H.-W. Ng,S. Winkler,,,,,,,,,,,icip2014a.pdf,http://vintage.winklerbros.net/Publications/icip2014a.pdf,
+face_tracer,FaceTracer,FaceTracer: A Search Engine for Large Collections of Images with Faces,,,,,,,,European Conference on Computer Vision (ECCV),,,2008,340-353,,N. Kumar,P. N. Belhumeur,S. K. Nayar,,,,,,,,1,,Kumar_ECCV08.pdf,http://www1.cs.columbia.edu/CAVE/publications/pdfs/Kumar_ECCV08.pdf,
+face_tracer,FaceTracer,Face Swapping: Automatically Replacing Faces in Photographs,,,,,,,,ACM Trans. on Graphics (also Proc. of ACM SIGGRAPH),,,2008,,,D. Bitouk,N. Kumar,S. Dhillon,P.N. Belhumeur,S. K. Nayar,,,,,,2,,Bitouk_SIGGRAPH08.pdf,http://www1.cs.columbia.edu/CAVE/publications/pdfs/Bitouk_SIGGRAPH08.pdf,
+facebook,SFC,,,,,"we don't have that, no paper",,,,,,,,,,,,,,,,,,,,,,,,
+facebook_100,Facebook100,Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+faceplace,Face Place,Recognizing disguised faces,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+faces94,Faces94,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+faces95,Faces95,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+faces96,Faces96,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+families_in_the_wild,FIW,Visual Kinship Recognition of Families in the Wild,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+fddb,FDDB,FDDB: A Benchmark for Face Detection in Unconstrained Settings,,,,,,,,"Technical Report UM-CS-2010-009, Dept. of Computer Science, University of Massachusetts",,,2010,,,Vidit Jain,Erik Learned-Mille,,,,,,,,,,,fddb.pdf,http://vis-www.cs.umass.edu/fddb/fddb.pdf,"@TechReport{fddbTech, + author = {Vidit Jain and Erik Learned-Miller}, + title = {FDDB: A Benchmark for Face Detection in Unconstrained Settings}, + institution = {University of Massachusetts, Amherst}, + year = {2010}, + number = {UM-CS-2010-009} + }"
+fei,FEI,Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro,,,,"in portugese, but original paper",,,,,,,,,,,,,,,,,,,,,,,,
+feret,FERET,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+ferplus,FER+,Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+fia,CMU FiA,The CMU Face In Action (FIA) Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+fiw_300,300-W,300 faces In-the-wild challenge: Database and results,,,,,,,,"Image and Vision Computing (IMAVIS), Special Issue on Facial Landmark Localisation ""In-The-Wild""",,,2016,,,C. Sagonas,E. Antonakos,"G, Tzimiropoulos",S. Zafeiriou,M. Pantic,,,,,,1,,,,
+fiw_300,300-W,300 Faces in-the-Wild Challenge: The first facial landmark localization Challenge,,,,,,,,"Proceedings of IEEE Int’l Conf. on Computer Vision (ICCV-W), 300 Faces in-the-Wild Challenge (300-W). Sydney, Australia",,,2013,,,C. Sagonas,G. Tzimiropoulos,S. Zafeiriou,M. Pantic,,,,,,,2,,,,
+fiw_300,300-W,A semi-automatic methodology for facial landmark annotation,,,,,,,,"Proceedings of IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR-W), 5th Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2013). Oregon, USA,",,,2013,,,C. Sagonas,G. Tzimiropoulos,S. Zafeiriou,M. Pantic,,,,,,,3,,,,
+florida_inmates,Florida Inmate,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+frav2d,FRAV2D,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+frav3d,FRAV3D,"MULTIMODAL 2D, 2.5D & 3D FACE VERIFICATION",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+frgc,FRGC,Overview of the Face Recognition Grand Challenge,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+gallagher,Gallagher,Clothing Cosegmentation for Recognizing People,,,,,,,,IEEE Conference on Computer Vision and Pattern Recognition,,,2008,,,Andrew Gallagher,Tsuhan Chen,,,,,,,,,,,141.pdf,,
+gavab_db,Gavab,GavabDB: a 3D face database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+geofaces,GeoFaces,GeoFaceExplorer: Exploring the Geo-Dependence of Facial Attributes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+georgia_tech_face_database,Georgia Tech Face,Maximum likelihood training of the embedded HMM for face detection and recognition,,,,"I think this is the correct paper – database was colected 1999, this is 2000",,,,,,,,,,,,,,,,,,,,,,,,
+gmu,Google Makeup,Parallel Optimized Pearson Correlation Condition (PO-PCC) for Robust Cosmetic Makeup Facial Recognition,,,,watermarked online publication,,,,,,,,,,,,,,,,,,,,,,,,
+google,Google (private),,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+graz,Graz Pedestrian,Generic Object Recognition with Boosting,,,,not sure which paper to use,,,,,,,,,,,,,,,,,,,,,,,,
+grimace,GRIMACE,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+h3d,H3D,Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+hda_plus,HDA+,The HDA+ data set for research on fully automated re-identification systems,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+hda_plus,HDA+,A Multi-camera video data set for research on High-Definition surveillance,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+helen,Helen,Interactive Facial Feature Localization,,,,,,,,ECCV,,,2012,,,Vuong Le,Jonathan Brandt,Zhe Lin,Lubomir Boudev,Thomas S. Huang,,,,,,,,eccv2012_helen_final.pdf,http://www.ifp.illinois.edu/~vuongle2/helen/eccv2012_helen_final.pdf,
+hi4d_adsip,Hi4D-ADSIP,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+hid_equinox_infrared,HID,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+hipsterwars,Hipsterwars,Hipster Wars: Discovering Elements of Fashion Styles,,,,,,,,In European Conference on Computer Vision,,,2014,,,M. Hadi Kiapour,Kota Yamaguchi,Alexander C. Berg,Tamara L. Berg,,,,,,,,,hipster_eccv14.pdf,http://tamaraberg.com/papers/hipster_eccv14.pdf,"@inproceedings{ + HipsterWarsECCV14, + title = {Hipster Wars: Discovering Elements of Fashion Styles} + author = {M. Hadi Kiapour, Kota Yamaguchi, Alexander C. Berg, Tamara L. Berg}, + booktitle={European Conference on Computer Vision}, + year = {2014} + }"
+hollywood_headset,HollywoodHeads,Context-aware {CNNs} for person head detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+hrt_transgender,HRT Transgender,Is the Eye Region More Reliable Than the Face? A Preliminary Study of Face-based Recognition on a Transgender Dataset,,,,No paper (asked for citation),,,,"In Proc. of IEEE Intl. Conf. on Biometrics: Theory, Applications, and Systems",,,2013,,,Gayathri Mahalingam,Karl Ricanek Jr.,,,,,,,,,,,,https://pdfs.semanticscholar.org/b066/733d533250f4ddafd22c12456def7fa24f4c.pdf,
+hrt_transgender,HRT Transgender,Investigating the Periocular-Based Face Recognition Across Gender Transformation,,,,No paper (asked for citation),,,,IEEE Trans. On Information Forensics and Security,,,2014,pp. 2180 – 2192,"vol. 9, no. 12",Gayathri Mahalingam,Karl Ricanek Jr.,Midori M. Albert,,,,,,,,,,,https://ieeexplore.ieee.org/document/6915725,
+hrt_transgender,HRT Transgender,Face recognition across gender transformation using SVM Classifier,,,,"Paper used for statistics, not mentionned in citations",,,,,,,,,,,,,,,,,,,,,,Face_Recognition_Across_Gender_Transformation_Usin.pdf,,
+ifad,IFAD,Indian Face Age Database: A Database for Face Recognition with Age Variation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ifdb,IFDB,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+iit_dehli_ear,IIT Dehli Ear,Automated human identification using ear imaging,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ijb_a,IJB-A,Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A ,,,,,,,,Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition,,,2015,1931-1939,07-12-June-2015,"Klare, B. F.","Klein, B.","Taborsky, E.","Blanton, A.","Cheney, J.","Allen, K., ... Jain, A. K.",,,,,,,Klare_Pushing_the_Frontiers_2015_CVPR_paper.pdf,http://ieeexplore.ieee.org/document/7298803/,"DOI: 10.1109/CVPR.2015.7298803 @inbook{882e95bdca414797b4a8e2bfcb5b1fa4, +title = ""Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A"", +abstract = ""Rapid progress in unconstrained face recognition has resulted in a saturation in recognition accuracy for current benchmark datasets. While important for early progress, a chief limitation in most benchmark datasets is the use of a commodity face detector to select face imagery. The implication of this strategy is restricted variations in face pose and other confounding factors. This paper introduces the IARPA Janus Benchmark A (IJB-A), a publicly available media in the wild dataset containing 500 subjects with manually localized face images. Key features of the IJB-A dataset are: (i) full pose variation, (ii) joint use for face recognition and face detection benchmarking, (iii) a mix of images and videos, (iv) wider geographic variation of subjects, (v) protocols supporting both open-set identification (1:N search) and verification (1:1 comparison), (vi) an optional protocol that allows modeling of gallery subjects, and (vii) ground truth eye and nose locations. The dataset has been developed using 1,501,267 million crowd sourced annotations. Baseline accuracies for both face detection and face recognition from commercial and open source algorithms demonstrate the challenge offered by this new unconstrained benchmark."", +author = ""Klare, {Brendan F.} and Ben Klein and Emma Taborsky and Austin Blanton and Jordan Cheney and Kristen Allen and Patrick Grother and Alan Mah and Mark Burge and Jain, {Anil K.}"", +year = ""2015"", +month = ""10"", +doi = ""10.1109/CVPR.2015.7298803"", +isbn = ""9781467369640"", +volume = ""07-12-June-2015"", +pages = ""1931--1939"", +booktitle = ""Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition"", +publisher = ""IEEE Computer Society"", + +} +"
+ijb_b,IJB-B,IARPA Janus Benchmark-B Face Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ijb_c,IJB-C,IARPA Janus Benchmark C,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ilids_mcts,,,,,,"government dataset, no paper that introduces the dataset",,,,,,,,,,,,,,,,,,,,,,,,
+ilids_vid_reid,iLIDS-VID,Person Re-Identi cation by Video Ranking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+images_of_groups,Images of Groups,Understanding Groups of Images of People,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+imdb_wiki,IMDB,Deep expectation of real and apparent age from a single image without facial landmarks,,,,,,,,International Journal of Computer Vision (IJCV),,6,2016,,,Rasmus Rothe,Radu Timofte,Luc Van Gool,,,,,,,,1,,eth_biwi_01299.pdf,,"@article{Rothe-IJCV-2016, + author = {Rasmus Rothe and Radu Timofte and Luc Van Gool}, + title = {Deep expectation of real and apparent age from a single image without facial landmarks}, + journal = {International Journal of Computer Vision (IJCV)}, + year = {2016}, + month = {July}, +}"
+imdb_wiki,IMDB,DEX: Deep EXpectation of apparent age from a single image,,,,,,,,IEEE International Conference on Computer Vision Workshops (ICCVW),,12,2015,,,Rasmus Rothe,Radu Timofte,Luc Van Gool,,,,,,,,2,,eth_biwi_01229.pdf,,"@InProceedings{Rothe-ICCVW-2015, + author = {Rasmus Rothe and Radu Timofte and Luc Van Gool}, + title = {DEX: Deep EXpectation of apparent age from a single image}, + booktitle = {IEEE International Conference on Computer Vision Workshops (ICCVW)}, + year = {2015}, + month = {December}, +}"
+imfdb,IMFDB,Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations,,,,,,,,"National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)",,,2013,,,Shankar Setty,et al,,,,,,,,,,,imfdb.pdf,http://cvit.iiit.ac.in/projects/IMFDB/imfdb.pdf,"@InProceedings{imfdb, +author = {Shankar Setty, Moula Husain, Parisa Beham, Jyothi Gudavalli, Menaka Kandasamy, Radhesyam Vaddi, Vidyagouri Hemadri, J C Karure, Raja Raju, Rajan, Vijay Kumar and C V Jawahar}, +title = {{I}ndian {M}ovie {F}ace {D}atabase: {A} {B}enchmark for {F}ace {R}ecognition {U}nder {W}ide {V}ariations}, +booktitle = {National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)}, +month = {Dec}, +year = {2013} +} "
+imm_face,IMM Face Dataset,The IMM Face Database - An Annotated Dataset of 240 Face Images,,,,,,,,"Informatics and Mathematical Modelling, Technical University of Denmark, DTU",,5,2004,,,Michael M. Nordstrøm,Mads Larsen,Janusz Sierakowski,Mikkel B. Stegmann,,,,,,,,,imm3160.pdf,,
+immediacy,Immediacy,Multi-task Recurrent Neural Network for Immediacy Prediction,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+imsitu,imSitu,Situation Recognition: Visual Semantic Role Labeling for Image Understanding,,,,,,,,"(1) Computer Science & Engineering, University of Washington, Seattle, WA +(2) Allen Institute for Artificial Intelligence (AI2), Seattle, WA",,,,,,Mark Yatskar,Luke Zettlemoyer,Ali Farhadi,,,,,,,,,,situations.pdf,https://homes.cs.washington.edu/~my89/publications/situations.pdf,
+inria_person,INRIA Pedestrian,Histograms of Oriented Gradients for Human Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+iqiyi,iQIYI-VID dataset ,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+jaffe,JAFFE,Coding Facial Expressions with Gabor Wavelets,,,,,,,,3rd IEEE International Conference on Automatic Face and Gesture Recognition,,,1998,200-205,,Michael J. Lyons,Shigeru Akemastu,Miyuki Kamachi,Jiro Gyoba,,,,,,,,,fg98-1.pdf,http://www.kasrl.org/fg98-1.pdf,
+jiku_mobile,Jiku Mobile Video Dataset,The Jiku Mobile Video Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+jpl_pose,JPL-Interaction dataset,First-Person Activity Recognition: What Are They Doing to Me?,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+karpathy_instagram,Karpathy Instagram,,,,,no paper / online project,,,,,,,,,,,,,,,,,,,,,,,,
+kdef,KDEF,The Karolinska Directed Emotional Faces – KDEF,,,,"this is the original paper form 1998 with this title, couldn't find it though, so not in nextcloud folder",,,,,,,,,,,,,,,,,,,,,,,,
+kin_face,UB KinFace,Genealogical Face Recognition based on UB KinFace Database,,,,"this is the original paper title, couldn't find it though, so not in nextcloud folder",,,,,,,,,,,,,,,,,,,,,,,,
+kin_face,UB KinFace,Kinship Verification through Transfer Learning,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+kin_face,UB KinFace,Understanding Kin Relationships in a Photo,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+kinectface,KinectFaceDB,KinectFaceDB: A Kinect Database for Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+kitti,KITTI,Vision meets Robotics: The KITTI Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+lag,LAG,Large Age-Gap Face Verification by Feature Injection in Deep Networks,,,,,,,,Pattern Recognition Letters,,,2017,36-42,90,Simone Bianco,,,,,,,,,,,,bianco2017large-age.pdf,http://www.ivl.disco.unimib.it/activities/large-age-gap-face-verification/,"@article{bianco2017large-age,
author = {Bianco, Simone},
year = {2017},
pages = {36-42},
title = {Large Age-Gap Face Verification by Feature Injection in Deep Networks},
volume = {90},
journal = {Pattern Recognition Letters},
doi = {10.1016/j.patrec.2017.03.006}}"
+large_scale_person_search,Large Scale Person Search,End-to-End Deep Learning for Person Search,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+leeds_sports_pose,Leeds Sports Pose,Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+leeds_sports_pose_extended,Leeds Sports Pose Extended,Learning Effective Human Pose Estimation from Inaccurate Annotation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+lfw,LFW,Labeled Faces in the Wild: A Survey,,,,,,,, ,,,,,,,,,,,,,,,,,,,,
+lfw,LFW,Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments,,,,,,,,"University of Massachusetts, Amherst, Technical Report ",,,2007,07-49,,Gary B. Huang,Manu Ramesh,Tamara Berg,Erik Learned-Miller,,,,,,,,various citaton depending on various datasets provided. Citation used here was first one published in 2007,lfw.pdf,http://vis-www.cs.umass.edu/lfw/lfw.pdf,
+lfw,LFW,Labeled Faces in the Wild: Updates and New Reporting Procedures,,,,,,,, ,,,,,,,,,,,,,,,,,,,,
+lfw_a,LFW-a,"Effective Unconstrained Face Recognition by
Combining Multiple Descriptors and Learned
Background Statistics",,,,,,,,"IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(10),",,,2011,,,Lior Wolf,Tal Hassner,Yaniv Taigman,,,,,,,,,,jpatchlbp.pdf,http://www.openu.ac.il/home/hassner/projects/Patchlbp/WolfHassnerTaigman_TPAMI11.pdf,Comply with any instructions specified for the original LFW data set
+lfw_p,LFWP,Localizing Parts of Faces Using a Consensus of Exemplars,,,,,,,,Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),,,2011,,,Peter N. Belhumeur,"David W. Jacobs,",David J. Kriegman,Neeraj Kumar,,,,,,,,,nk_cvpr2011_faceparts.pdf,http://neerajkumar.org/projects/face-parts/base/papers/nk_cvpr2011_faceparts.pdf,
+lfwa_plus,LFWA+,,,,,"no paper, no details",,,,,,,,,,,,,,,,,,,,,,,,
+m2vts,m2vts,The M2VTS Multimodal Face Database (Release 1.00),,,,,,,,,,,,,,,,,,,,,,,,,,,,
+m2vtsdb_extended,xm2vtsdb,XM2VTSDB: The Extended M2VTS Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mafl,MAFL,Facial Landmark Detection by Deep Multi-task Learning,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mafl,MAFL,Learning Deep Representation for Face Alignment with Auxiliary Attributes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+malf,MALF,Fine-grained Evaluation on Face Detection in the Wild.,,,,,,,,Proceedings of the 11th IEEE International Conference on Automatic Face and Gesture Recognition Conference and Workshops.,,,2015,,,Bin Yang*,Junjie Yan*,Zhen Lei,Stan Z. Li,,,,,,,,,faceevaluation15.pdf,http://www.cbsr.ia.ac.cn/faceevaluation/faceevaluation15.pdf,"@inproceedings{faceevaluation15, +title={Fine-grained Evaluation on Face Detection in the Wild}, +author={Yang, Bin and Yan, Junjie and Lei, Zhen and Li, Stan Z}, +booktitle={Automatic Face and Gesture Recognition (FG), 11th IEEE International +Conference on}, +year={2015}, +organization={IEEE} +}"
+mapillary,Mapillary,The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+market_1501,Market 1501,Scalable Person Re-identification: A Benchmark,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+market1203,Market 1203,Orientation Driven Bag of Appearances for Person Re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mars,MARS,MARS: A Video Benchmark for Large-Scale Person Re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mcgill,McGill Real World,Hierarchical Temporal Graphical Model for Head Pose Estimation and Subsequent Attribute Classification in Real-World Videos,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mcgill,McGill Real World,Robust Semi-automatic Head Pose Labeling for Real-World Face Video Sequences,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+meds,Multiple Encounter Dataset,MEDS: Multiple Encounter Dataset (Deceased Persons),,,,"not a paper, more like a report",,,,,,,,,,,,,,,,,,,,,,,,
+megaage,MegaAge,Quantifying Facial Age by Posterior of Age Comparisons,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+megaface,MegaFace,The MegaFace Benchmark: 1 Million Faces for Recognition at Scale ,,,,The 2 papers refer to respectively: MF and MF2 ,,,,IEEE Conference on Computer Vision and Pattern Recognition (CVPR),,,2017,,,"Nech, Aaron","Kemelmacher-Shlizerman, Ira",,,,,,,,,If you're participating or using data from Challenge 2 please cite:,,1705.00393.pdf,https://homes.cs.washington.edu/~kemelmi/ms.pdf,"@inproceedings{nech2017level, +title={Level Playing Field For Million Scale Face Recognition}, +author={Nech, Aaron and Kemelmacher-Shlizerman, Ira}, +booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, +year={2017} +}"
+megaface,MegaFace,Level Playing Field for Million Scale Face Recognition ,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mifs,MIFS,Spoofing Faces Using Makeup: An Investigative Study,,,,,,,,"Proc. of 3rd IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), (New Delhi, India)",,,2017,,,C. Chen,A. Dantcheva,T. Swearingen,A. Ross,,,,,,,,,,http://www.cse.msu.edu/~rossarun/pubs/ChenFaceMakeupSpoof_ISBA2017.pdf,
+mikki,MIKKI dataset,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+mit_cbcl,MIT CBCL,Component-based Face Recognition with 3D Morphable Models,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mit_cbcl_ped,CBCL,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+mit_cbclss,CBCLSS,,,,,no paper but PhD Thesis presenting the DB,,,,,,,,,,,,,,,,,,,,,,,,
+miw,MIW,Automatic Facial Makeup Detection with Application in Face Recognition,,,,,,,,"Proc. of 6th IAPR International Conference on Biometrics (ICB), (Madrid, Spain)",,,2013,,,C. Chen,A. Dantcheva,A. Ross,,,,,,,,,,,https://www.cse.msu.edu/~rossarun/pubs/ChenMakeupDetection_ICB2013.pdf,
+mmi_facial_expression,MMI Facial Expression Dataset,WEB-BASED DATABASE FOR FACIAL EXPRESSION ANALYSIS,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+moments_in_time,Moments in Time,Moments in Time Dataset: one million videos for event understanding,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+morph,MORPH Commercial,MORPH: A Longitudinal Image Database of Normal Adult Age-Progression,,,,same pdf as morph non commercial,,,,"IEEE 7th International Conference on Automatic Face and Gesture Recognition, Southampton, UK",,,2006,341-345,,Karl Ricanek Jr,Tamirat Tesafaye,,,,,,,,,,,,,
+morph_nc,MORPH Non-Commercial,MORPH: A Longitudinal Image Database of Normal Adult Age-Progression,,,,same pdf as morph commercial,,,,"IEEE 7th International Conference on Automatic Face and Gesture Recognition, Southampton, UK",,,2006,341-345,,Karl Ricanek Jr,Tamirat Tesafaye,,,,,,,,,,,,,
+mot,MOT,Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics,,,,these 3 citations are from the MOT17,,,,,,,,,,,,,,,,,,,,,,,,
+mot,MOT,"Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mot,MOT,Learning to associate: HybridBoosted multi-target tracker for crowded scene,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mpi_large,Large MPI Facial Expression,The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mpi_small,Small MPI Facial Expression,The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mpii_gaze,MPIIGaze,Appearance-based Gaze Estimation in the Wild,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mpii_human_pose,MPII Human Pose,2D Human Pose Estimation: New Benchmark and State of the Art Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mr2,MR2,The MR2: A multi-racial mega-resolution database of facial stimuli,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mrp_drone,MRP Drone,Investigating Open-World Person Re-identification Using a Drone,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+msceleb,MsCeleb,MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,,,,,,,,European Conference on Computer Vision,,,2016,,,"Guo, Yandong","Zhang, Lei","Hu, Yuxiao","He, Xiaodong","Gao, Jianfeng",,,,,,,,,https://www.microsoft.com/en-us/research/wp-content/uploads/2016/08/MSCeleb-1M-a.pdf,"@INPROCEEDINGS { guo2016msceleb, + author = {Guo, Yandong and Zhang, Lei and Hu, Yuxiao and He, Xiaodong and Gao, Jianfeng}, + title = {M{S}-{C}eleb-1{M}: A Dataset and Benchmark for Large Scale Face Recognition}, + booktitle = {European Conference on Computer Vision}, + year = {2016}, + organization={Springer}}"
+msmt_17,MSMT17,Person Trasfer GAN to Bridge Domain Gap for Person Re-Identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+muct,MUCT,The MUCT Landmarked Face Database,,,,,,,,Pattern Recognition Association of South Africa,,,2010,,,,S. Milborrow,J. Morkel,F. Nicolls,,,,,,,,,,http://www.milbo.org/muct/The-MUCT-Landmarked-Face-Database.pdf,"@article{Milborrow10, + author={S. Milborrow and J. Morkel and F. Nicolls}, + title={{The MUCT Landmarked Face Database}}, + journal={Pattern Recognition Association of South Africa}, + year=2010, + note={\url{http://www.milbo.org/muct}} +}"
+mug_faces,MUG Faces,The MUG Facial Expression Database,,,,,,,,Procedings of 11th International Workshop on Image Analysis for Multimedia Interactive Services,12,4,2010,,,N. Aifanti,C. Papachristou,A. Delopoulos,,,,,,,,,,,,
+multi_pie,MULTIPIE,Multi-PIE,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+mtfl,MTFL,Facial Landmark Detection by Deep Multi-task Learning,,,,same paper as in MAFL,,,,,,,,,,,,,,,,,,,,,,,,
+mtfl,MTFL,Learning Deep Representation for Face Alignment with Auxiliary Attributes,,,,same papers as in MAFL,,,,,,,,,,,,,,,,,,,,,,,,
+names_and_faces_news,News Dataset,Names and Faces,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+nd_2006,ND-2006,Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+nist_mid_mugshot,MID,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+nova_emotions,Novaemötions Dataset,Crowdsourcing facial expressions for affective-interaction,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+nova_emotions,Novaemötions Dataset,Competitive affective gamming: Winning with a smile,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+nudedetection,Nude Detection,A Bag-of-Features Approach based on Hue-SIFT Descriptor for Nude Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+orl,ORL,Parameterisation of a Stochastic Model for Human Face Identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+penn_fudan,Penn Fudan,Object Detection Combining Recognition and Segmentation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+peta,PETA,Pedestrian Attribute Recognition At Far Distance,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pets,PETS 2017,PETS 2017: Dataset and Challenge,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pilot_parliament,PPB,Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classi cation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pipa,PIPA,Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues,,,,,,,,arXiv:1501.05703 [cs.CV],,,2015,,,Ning Zhang, Manohar Paluri,Yaniv Taigman,Rob Fergus,Lubomir Bourdev,,,,,,,,,https://arxiv.org/pdf/1501.05703.pdf,"@inproceedings{piper, + Author = {Ning Zhang and Manohar Paluri and Yaniv Taigman and Rob Fergus and Lubomir Bourdev}, + Title = {Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues}, + Eprint = {arXiv:1501.05703}, + Year = {2015}}"
+pku,PKU,Swiss-System Based Cascade Ranking for Gait-based Person Re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pku_reid,PKU-Reid,Orientation driven bag of appearances for person re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pornodb,Pornography DB,Pooling in Image Representation: the Visual Codeword Point of View,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+precarious,Precarious,Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+prid,PRID,Person Re-Identification by Descriptive and Discriminative Classification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+prw,PRW,Person Re-identification in the Wild,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+psu,PSU,Vision-based Analysis of Small Groups in Pedestrian Crowds,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+pubfig,PubFig,Attribute and Simile Classifiers for Face Verification,,,,,,,,International Conference on Computer Vision (ICCV),,,2009,,,Neeraj Kumar,Alexander C. Berg,Peter N. Belhumeur,Shree K. Nayar,,,,,,,,,,http://www.cs.columbia.edu/CAVE/publications/pdfs/Kumar_ICCV09.pdf,
+pubfig_83,pubfig83,Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+put_face,Put Face,The PUT face database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+qmul_grid,GRID,Multi-Camera Activity Correlation Analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+qmul_grid,GRID,Time-delayed correlation analysis for multi-camera activity understanding,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+qmul_ilids,QMUL-iLIDS,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+qmul_surv_face,QMUL-SurvFace,Surveillance Face Recognition Challenge,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+rafd,RaFD,Presentation and validation of the Radboud Faces Database,,,,,,,,Cognition & Emotion,,,2010,1377-1388,24.8,"Langner, O.","Dotsch, R."," Bijlstra, G.","Wigboldus, D.H.J.","Hawk, S.T.","van Knippenberg, A.",,,,,,,,http://dx.doi.org/10.1080/02699930903485076,DOI: 10.1080/02699930903485076
+raid,RAiD,Consistent Re-identification in a Camera Network,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+rap_pedestrian,RAP,A Richly Annotated Dataset for Pedestrian Attribute Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+reseed,ReSEED,ReSEED: Social Event dEtection Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+saivt,SAIVT SoftBio,A Database for Person Re-Identification in Multi-Camera Surveillance Networks,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sarc3d,Sarc3D,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+scface,SCface,SCface – surveillance cameras face database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+scut_fbp,SCUT-FBP,SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception,,,,,,,,arXiv:1511.02459 [cs.CV],,,2015,,,Duorui Xie,Lingyu Liang,Lianwen Jin,Jie Xu,Mengru Li,,,,,,,,,https://arxiv.org/ftp/arxiv/papers/1511/1511.02459.pdf,
+scut_head,SCUT HEAD,Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sdu_vid,SDU-VID,A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sdu_vid,SDU-VID,Local descriptors encoded by Fisher vectors for person re-identification,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sdu_vid,SDU-VID,Person reidentification by video ranking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sheffield,Sheffield Face,Face Recognition: From Theory to Applications ,,,,paper within a book - no pdf,,,,,,,,,,,,,,,,,,,,,,,,
+shinpuhkan_2014,Shinpuhkan 2014,Shinpuhkan2014: A Multi-Camera Pedestrian Dataset for Tracking People across Multiple Cameras,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+social_relation,Social Relation,From Facial Expression Recognition to Interpersonal Relation Prediction,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+social_relation,Social Relation,Learning Social Relation Traits from Face Images,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+soton,SOTON HiD,On a Large Sequence-Based Human Gait Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sports_videos_in_the_wild,SVW,Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis,,,,,,,,"Proc. International Conference on Automatic Face and Gesture Recognition (FG 2015), Ljubljana, Slovenia",,,2015,,,Seyed Morteza Safdarnejad, Xiaoming Liu, Lalita Udpa, Brooks Andrus,"John Wood,",Dean Craven,,,,,,,,http://cvlab.cse.msu.edu/pdfs/Morteza_FG2015.pdf," @inproceedings{ sports-videos-in-the-wild-svw-a-video-dataset-for-sports-analysis, + author = { Seyed Morteza Safdarnejad and Xiaoming Liu and Lalita Udpa and Brooks Andrus and John Wood and Dean Craven }, + title = { Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis }, + booktitle = { Proc. International Conference on Automatic Face and Gesture Recognition }, + address = { Ljubljana, Slovenia }, + month = { May }, + year = { 2015 }, +} "
+stair_actions,STAIR Action,"STAIR Actions: A Video Dataset of Everyday +Home Actions",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stanford_drone,Stanford Drone,Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stickmen_buffy,Buffy Stickmen,Learning to Parse Images of Articulated Objects,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stickmen_buffy,Buffy Stickmen,Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stickmen_family,We Are Family Stickmen,We Are Family: Joint Pose Estimation of Multiple Persons,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stickmen_pascal,Stickmen PASCAL,Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stickmen_pascal,Stickmen PASCAL,Learning to Parse Images of Articulated Objects,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+stirling_esrc_3s,Stirling/ESRC 3D Face,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+sun_attributes,SUN,The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+sun_attributes,SUN,"SUN Attribute Database:
Discovering, Annotating, and Recognizing Scene Attributes",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+svs,SVS,,,,,no paper,,,,,,,,,,,,,,,,,,,,,,,,
+texas_3dfrd,Texas 3DFRD,Texas 3D Face Recognition Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+texas_3dfrd,Texas 3DFRD,Anthropometric 3D Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tiny_faces,TinyFace,Low-Resolution Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tiny_images,Tiny Images,"80 million tiny images: a large dataset for
non-parametric object and scene recognition",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+towncenter,TownCenter,Stable Multi-Target Tracking in Real-Time Surveillance Video,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_brussels,TUD-Brussels,Multi-Cue Onboard Pedestrian Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_campus,TUD-Campus, People-Tracking-by-Detection and People-Detection-by-Tracking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_crossing,TUD-Crossing, People-Tracking-by-Detection and People-Detection-by-Tracking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_motionpairs,TUD-Motionparis,Multi-Cue Onboard Pedestrian Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_multiview,TUD-Multiview,Monocular 3D Pose Estimation and Tracking by Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_pedestrian,TUD-Pedestrian, People-Tracking-by-Detection and People-Detection-by-Tracking,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tud_stadtmitte,TUD-Stadtmitte,Monocular 3D Pose Estimation and Tracking by Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+tvhi,TVHI,High Five: Recognising human interactions in TV shows,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+twinsburg_twins,ND-TWINS-2009-2010,,,,,"No Paper. As found in License Agreement: 5.Citation: All documents and papers that report on research that uses the UND Biometrics Database must acknowledge +the use of the database by including the citation as given by the UND Principal Investigator.",,,,,,,,,,,,,,,,,,,,,,,,
+uccs,UCCS,Large scale unconstrained open set face database,,,,need research access to the paper,,,,,,,,,,,,,,,,,,,,,,,,
+ucf_101,UCF101,UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild,,,,,,,,CRCV-TR-12-01,,,2012,,,"Soomro, K.","Roshan Zamir, A.","Shah, M.",,,,,,,,2,,,,"@inproceedings{UCF101, + author = {Soomro, K. and Roshan Zamir, A. and Shah, M.}, + booktitle = {CRCV-TR-12-01}, + title = {{UCF101}: A Dataset of 101 Human Actions Classes From + Videos in The Wild}, + year = {2012}}"
+ucf_crowd,UCF-CC-50, Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ucf_selfie,UCF Selfie,How to Take a Good Selfie?,,,,,,,," in Proceedings of ACM Multimedia Conference 2015 (ACMMM 2015), Brisbane, Australia",,,2015,,,Mahdi M. Kalayeh,Misrak Seifu,Wesna LaLanne,Mubarak Shah,,,,,,,,,,,
+ufdd,UFDD,Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+umb,UMB,UMB-DB: A Database of Partially Occluded 3D Faces,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+umd_faces,UMD,UMDFaces: An Annotated Face Dataset for Training Deep Networks,,,,,,,,Arxiv preprint,,,2016,,,Ankan Bansal,Anirudh Nanduri,Carlos D Castillo,Rajeev Ranjan,Rama Chellappa,,,,,,1,,,https://arxiv.org/abs/1611.01484v2,"@article{bansal2016umdfaces, + title={UMDFaces: An Annotated Face Dataset for Training Deep Networks}, + author={Bansal, Ankan and Nanduri, Anirudh and Castillo, Carlos D and Ranjan, Rajeev and Chellappa, Rama} + journal={arXiv preprint arXiv:1611.01484v2}, + year={2016} + }"
+umd_faces,UMD,The Do's and Don'ts for CNN-based Face Verification,,,,,,,,Arxiv preprint,,,2017,,,Ankan Bansal,Carlos Castillo,"Rajeev Ranjan,",Rama Chellappa,,,,,,,2,,,https://arxiv.org/abs/1705.07426,"@article{bansal2017dosanddonts, + title = {The Do's and Don'ts for CNN-based Face Verification}, + author = {Bansal, Ankan and Castillo, Carlos and Ranjan, Rajeev and Chellappa, Rama}, + journal = {arXiv preprint arXiv:1705.07426}, + year = {2017} + }"
+unbc_shoulder_pain,UNBC-McMaster Pain,PAINFUL DATA: The UNBC-McMaster Shoulder Pain Expression Archive Database,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+urban_tribes,Urban Tribes,From Bikers to Surfers: Visual Recognition of Urban Tribes,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+used,USED Social Event Dataset,USED: A Large-scale Social Event Detection Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+v47,V47,Re-identification of Pedestrians with Variable Occlusion and Scale,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vadana,VADANA,VADANA: A dense dataset for facial image analysis,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vgg_celebs_in_places,CIP,Faces in Places: Compound Query Retrieval ,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vgg_faces,VGG Face,Deep Face Recognition,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vgg_faces2,VGG Face2,VGGFace2: A dataset for recognising faces across pose and age,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+violent_flows,Violent Flows,Violent Flows: Real-Time Detection of Violent Crowd Behavior,,,,,,,,,,,2012,,,T. Hassner,,,,,,,,,,,,,,"T. Hassner, Y. Itcher, and O. Kliper-Gross, Violent Flows: Real-Time Detection of Violent Crowd Behavior, 3rd IEEE International Workshop on Socially Intelligent Surveillance and Monitoring (SISM) at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Rhode Island, June 2012 ."
+viper,VIPeR,"Evaluating Appearance Models for Recognition, Reacquisition, and Tracking",,,,,,,,,,,,,,,,,,,,,,,,,,,,
+visual_phrases,Phrasal Recognition,Recognition using Visual Phrases,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vmu,VMU,Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?,,,,,,,,"Proc. of 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Washington DC, USA)",,,2012,,,A. Dantcheva,C. Chen,A. Ross,,,,,,,,,,,https://www.cse.msu.edu/~rossarun/pubs/DantchevaChenRossFaceCosmetics_BTAS2012.pdf,
+voc,VOC,The PASCAL Visual Object Classes (VOC) Challenge,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+vqa,VQA,VQA: Visual Question Answering,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+ward,WARD,Re-identify people in wide area camera network,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+who_goes_there,WGT,Who Goes There? Approaches to Mapping Facial Appearance Diversity,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+wider,WIDER,Recognize Complex Events from Static Images by Fusing Deep Channels,,,,,,,,2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),,,2015,,,"Xiong, Yuanjun and Zhu, Kai and Lin, Dahua and Tang, Xiaoou",,,,,,,,,,,,,,
+wider_attribute,WIDER Attribute,Human Attribute Recognition by Deep Hierarchical Contexts,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+wider_face,WIDER FACE,WIDER FACE: A Face Detection Benchmark,,,,,,,,IEEE Conference on Computer Vision and Pattern Recognition (CVPR),,,2016,,,"Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou",,,,,,,,,,,,,,"@inproceedings{yang2016wider, + Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou}, + Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, + Title = {WIDER FACE: A Face Detection Benchmark}, + Year = {2016}}"
+wildtrack,WildTrack, WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+yale_faces,YaleFaces,,,,,no paper,,,,"IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Face Recognition",,,1997,711--720,17(7),P. N. Bellhumer,J. Hespanha,D. Kriegman,,,,,,,,,,,,
+yale_faces_b,Yale Face Database B,Acquiring Linear Subspaces for Face Recognition under Variable Lighting,,,,,,,,PAMI,,,2001,,,Athinodoros Georghiades,Peter Belhumeur,David Kriegman,,,,,,,,,,,,
+yale_faces_b_ext,Extended Yale Face Database B ,From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+yawdd,YawDD,YawDD: A Yawning Detection Dataset,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+yfcc_100m,YFCC100M,YFCC100M: The New Data in Multimedia Research,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+york_3d,UOY 3D Face Database,Three-Dimensional Face Recognition: An Eigensurface Approach,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+youtube_faces,YouTubeFaces,Face Recognition in Unconstrained Videos with Matched Background Similarity,,,,,,,,IEEE Conf. on Computer Vision and Pattern Recognition (CVPR),,,2011,,,Lior Wolf,Tal Hassner,Itay Maoz,,,,,,,,,,,,
+youtube_makeup,YMU,Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?,,,,,,,,"Proc. of 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Washington DC, USA)",,,2012,,,A. Dantcheva,C. Chen,A. Ross,,,,,,,,1,,,https://www.cse.msu.edu/~rossarun/pubs/DantchevaChenRossFaceCosmetics_BTAS2012.pdf,
+youtube_makeup,YMU,Automatic Facial Makeup Detection with Application in Face Recognition,,,,,,,,"Proc. of 6th IAPR International Conference on Biometrics (ICB), (Madrid, Spain)",,,2013,,,C. Chen,A. Dantcheva,A. Ross,,,,,,,,2,,,https://www.cse.msu.edu/~rossarun/pubs/ChenMakeupDetection_ICB2013.pdf,
+youtube_poses,YouTube Pose,Personalizing Human Video Pose Estimation,,,,The paper doesn't specifically introduce the dataset but it's the only one talking about it,,,,,,,,,,,,,,,,,,,,,,,,
\ No newline at end of file diff --git a/scraper/datasets/citations-3.csv b/scraper/datasets/citations-3.csv deleted file mode 100644 index 57db254d..00000000 --- a/scraper/datasets/citations-3.csv +++ /dev/null @@ -1,51 +0,0 @@ -Database Name,Title,Journal/Pub/Conference,Year,Pages,Volume,Author1,Author2,Author3,Author4,Author5,Author 6,PDF,Priority,URL,bibtex_reference_only,notes
-imSitu,Situation Recognition: Visual Semantic Role Labeling for Image Understanding,"(1) Computer Science & Engineering, University of Washington, Seattle, WA -(2) Allen Institute for Artificial Intelligence (AI2), Seattle, WA",,,,Mark Yatskar,Luke Zettlemoyer,Ali Farhadi,,,,,,https://homes.cs.washington.edu/~my89/publications/situations.pdf,,
-JAFFE,Coding Facial Expressions with Gabor Wavelets,3rd IEEE International Conference on Automatic Face and Gesture Recognition,1998,200-205,,Michael J. Lyons,Shigeru Akemastu,Miyuki Kamachi,Jiro Gyoba,,,,,http://www.kasrl.org/fg98-1.pdf,,
-UCF101,THUMOS Challenge: Action Recognition with a Large Number of Classes,,2015,,,"Gorban, A.","Idrees, H.","Jiang, Y.-G.","Roshan Zamir, A.","Laptev, I.","Shah, M. and Sukthankar, R.",,1,http://www.thumos.info/,"@misc{THUMOS15, - author = ""Gorban, A. and Idrees, H. and Jiang, Y.-G. and Roshan Zamir, A. and Laptev, - I. and Shah, M. and Sukthankar, R."", - title = ""{THUMOS} Challenge: Action Recognition with a Large - Number of Classes"", - howpublished = ""\url{http://www.thumos.info/}"", - Year = {2015}}",
-IMFDB,Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations,"National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)",2013,,,Shankar Setty,et al,,,,,,,http://cvit.iiit.ac.in/projects/IMFDB/imfdb.pdf,"@InProceedings{imfdb, -author = {Shankar Setty, Moula Husain, Parisa Beham, Jyothi Gudavalli, Menaka Kandasamy, Radhesyam Vaddi, Vidyagouri Hemadri, J C Karure, Raja Raju, Rajan, Vijay Kumar and C V Jawahar}, -title = {{I}ndian {M}ovie {F}ace {D}atabase: {A} {B}enchmark for {F}ace {R}ecognition {U}nder {W}ide {V}ariations}, -booktitle = {National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)}, -month = {Dec}, -year = {2013} -} ",
-LFW-a,Effective Face Recognition by Combining Multiple Descriptors and Learned Background Statistics,"IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(10),",2011,,,Lior Wolf,Tal Hassner,Yaniv Taigman,,,,,,http://www.openu.ac.il/home/hassner/projects/Patchlbp/WolfHassnerTaigman_TPAMI11.pdf,,
-MORPH commercial,MORPH: A Longitudinal Image Database of Normal Adult Age-Progression,"IEEE 7th International Conference on Automatic Face and Gesture Recognition, Southampton, UK",2006,341-345,,Karl Ricanek Jr,Tamirat Tesafaye,,,,,,,,,
-SCUT-FBP,SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception,arXiv:1511.02459 [cs.CV],2015,,,Duorui Xie,Lingyu Liang,Lianwen Jin,Jie Xu,Mengru Li,,,,https://arxiv.org/ftp/arxiv/papers/1511/1511.02459.pdf,,
-Names and Faces,Names and Faces in the News,"Computer Vision and Pattern Recognition (CVPR), Washington D.C.",2004,848-854,,Tamara L. Berg,Alexander C. Berg,Jaety Edwards,Michael Maire,Ryan White,"Yee Whye Teh, Erik Learned-Miller, David A. Forsyth",,3,http://www.cs.berkeley.edu/%7Eaberg/papers/berg_names_and_faces.pdf,,
-FaceScrub,A data-driven approach to cleaning large face datasets,Proc. IEEE International Conference on Image Processing (ICIP),2014,,,H.-W. Ng,S. Winkler,,,,,,,,,
-UCF Selfie,"How to Take a Good Selfie?, in Proceedings of ACM Multimedia Conference 2015 (ACMMM 2015), Brisbane, Australia",,2015,,,Mahdi M. Kalayeh,Misrak Seifu,Wesna LaLanne,Mubarak Shah,,,,,,,
-300-W,A semi-automatic methodology for facial landmark annotation,"Proceedings of IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR-W), 5th Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2013). Oregon, USA,",2013,,,C. Sagonas,G. Tzimiropoulos,S. Zafeiriou,M. Pantic,,,,3,,,
-YMU,Automatic Facial Makeup Detection with Application in Face Recognition,"Proc. of 6th IAPR International Conference on Biometrics (ICB), (Madrid, Spain)",2013,,,C. Chen,A. Dantcheva,A. Ross,,,,,2,https://www.cse.msu.edu/~rossarun/pubs/ChenMakeupDetection_ICB2013.pdf,,
-WIDER,Recognize Complex Events from Static Images by Fusing Deep Channels,2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2015,,,"Xiong, Yuanjun and Zhu, Kai and Lin, Dahua and Tang, Xiaoou",,,,,,,,,,
-YaleFaces,Eigenfaces vs. fisherfaces: Recognition using class specific linear projection,"IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Face Recognition",1997,711--720,17(7),P. N. Bellhumer,J. Hespanha,D. Kriegman,,,,,,,,
-PubFig,Attribute and Simile Classifiers for Face Verification,International Conference on Computer Vision (ICCV),2009,,,Neeraj Kumar,Alexander C. Berg,Peter N. Belhumeur,Shree K. Nayar,,,,,http://www.cs.columbia.edu/CAVE/publications/pdfs/Kumar_ICCV09.pdf,,
-Face Research Lab London Set,Face Research Lab London Set. figshare,,2017,,,"DeBruine, Lisa","Jones, Benedict",,,,,,,https://doi.org/10.6084/m9.figshare.5047666.v3,,
-MALF,Fine-grained Evaluation on Face Detection in the Wild.,Proceedings of the 11th IEEE International Conference on Automatic Face and Gesture Recognition Conference and Workshops.,2015,,,Bin Yang*,Junjie Yan*,Zhen Lei,Stan Z. Li,,,,,http://www.cbsr.ia.ac.cn/faceevaluation/faceevaluation15.pdf,"@inproceedings{faceevaluation15, -title={Fine-grained Evaluation on Face Detection in the Wild}, -author={Yang, Bin and Yan, Junjie and Lei, Zhen and Li, Stan Z}, -booktitle={Automatic Face and Gesture Recognition (FG), 11th IEEE International -Conference on}, -year={2015}, -organization={IEEE} -}",
-FaceScrub,A data-driven approach to cleaning large face datasets,"Proc. IEEE International Conference on Image Processing (ICIP), Paris, France",2014,,,H.-W. Ng,S. Winkler,,,,,,,http://vintage.winklerbros.net/Publications/icip2014a.pdf,,
-VMU,Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?,"Proc. of 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Washington DC, USA)",2012,,,A. Dantcheva,C. Chen,A. Ross,,,,,,https://www.cse.msu.edu/~rossarun/pubs/DantchevaChenRossFaceCosmetics_BTAS2012.pdf,,
-300-W,300 faces In-the-wild challenge: Database and results,"Image and Vision Computing (IMAVIS), Special Issue on Facial Landmark Localisation ""In-The-Wild""",2016,,,C. Sagonas,E. Antonakos,"G, Tzimiropoulos",S. Zafeiriou,M. Pantic,,,1,,,
-CK,Comprehensive Database for Facial Expression Analysis,"Proceedings of the Fourth IEEE International Conferenc -e on Automatic Face and Gesture Recognition -(FG'00) -",2000,484-490,,"Kanade, T.","Cohn, J. F.","Tian, Y.",,,,,,http://www.pitt.edu/~jeffcohn/biblio/Cohn-Kanade_Database.pdf,,
-MegaFace 2,Level Playing Field for Million Scale Face Recognition,IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017,,,"Nech, Aaron","Kemelmacher-Shlizerman, Ira",,,,,,If you're participating or using data from Challenge 2 please cite:,https://homes.cs.washington.edu/~kemelmi/ms.pdf,"@inproceedings{nech2017level, -title={Level Playing Field For Million Scale Face Recognition}, -author={Nech, Aaron and Kemelmacher-Shlizerman, Ira}, -booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, -year={2017} -}",
diff --git a/scraper/datasets/citations.csv b/scraper/datasets/citations.csv index a2ab42cc..c8019514 120000 --- a/scraper/datasets/citations.csv +++ b/scraper/datasets/citations.csv @@ -1 +1 @@ -citations-2018310.csv
\ No newline at end of file +citations-20181207.csv
\ No newline at end of file diff --git a/scraper/s2-papers.py b/scraper/s2-papers.py index f38bb800..bf77a734 100644 --- a/scraper/s2-papers.py +++ b/scraper/s2-papers.py @@ -42,23 +42,5 @@ def fetch_papers(index, depth): paper = fetch_paper(paper_id) # get all of the paper's citations -def fetch_paper(paper_id): - os.makedirs('./datasets/s2/papers/{}/{}'.format(paper_id[0:2], paper_id), exist_ok=True) - paper_fn = './datasets/s2/papers/{}/{}/paper.json'.format(paper_id[0:2], paper_id) - if os.path.exists(paper_fn): - return read_json(paper_fn) - print(paper_id) - paper = s2.paper(paper_id) - if paper is None: - print("Got none paper??") - time.sleep(random.randint(20, 30)) - paper = s2.paper(paper_id) - if paper is None: - print("Paper not found") - return None - write_json(paper_fn, paper) - time.sleep(random.randint(5, 10)) - return paper - if __name__ == '__main__': fetch_papers() diff --git a/scraper/s2-search.py b/scraper/s2-search.py index ddecf2f9..169a8d19 100644 --- a/scraper/s2-search.py +++ b/scraper/s2-search.py @@ -7,7 +7,7 @@ import random import re import simplejson as json import click -from s2 import SemanticScholarAPI +from s2 import SemanticScholarAPI, fetch_paper from util import * ''' @@ -33,6 +33,8 @@ def fetch_entries(index): key = line[0] name = line[1] title = re.sub(r'[^-0-9a-zA-Z ]+', '', line[2]) + if len(title) < 2: + continue dump_fn = './datasets/s2/dumps/{}.json'.format(key) entry_fn = './datasets/s2/entries/{}.json'.format(key) result = None @@ -49,7 +51,7 @@ def fetch_entries(index): write_json(entry_fn, result) if result: paper_id = result['id'] - paper = fetch_paper(paper_id) + paper = fetch_paper(s2, paper_id) citation_lookup.append([key, name, title, paper_id]) write_csv("datasets/citation_lookup.csv", keys=['key', 'name', 'title', 'paper_id'], rows=citation_lookup) diff --git a/scraper/s2.py b/scraper/s2.py index ea090845..21c3a7aa 100644 --- a/scraper/s2.py +++ b/scraper/s2.py @@ -1,5 +1,8 @@ import os import requests +import time +import random +from util import * class AuthorStub(object): @@ -192,3 +195,21 @@ class SemanticScholarAPI(object): }, headers=SemanticScholarAPI.headers) # print(resp.status_code) return None if resp.status_code != 200 else resp.json() + +def fetch_paper(s2, paper_id): + os.makedirs('./datasets/s2/papers/{}/{}'.format(paper_id[0:2], paper_id), exist_ok=True) + paper_fn = './datasets/s2/papers/{}/{}/paper.json'.format(paper_id[0:2], paper_id) + if os.path.exists(paper_fn): + return read_json(paper_fn) + print(paper_id) + paper = s2.paper(paper_id) + if paper is None: + print("Got none paper??") + time.sleep(random.randint(1, 2)) + paper = s2.paper(paper_id) + if paper is None: + print("Paper not found") + return None + write_json(paper_fn, paper) + time.sleep(random.randint(1, 2)) + return paper |