diff options
Diffstat (limited to 'site/datasets/unknown/wider_face.json')
| -rw-r--r-- | site/datasets/unknown/wider_face.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/unknown/wider_face.json b/site/datasets/unknown/wider_face.json index c7af0f1f..889050dc 100644 --- a/site/datasets/unknown/wider_face.json +++ b/site/datasets/unknown/wider_face.json @@ -1 +1 @@ -{"id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "citations": [{"id": "c9c9ade2ef4dffb7582a629a47ea70c31be7a35e", "title": "Detecting Faces Using Inside Cascaded Contextual CNN", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_Detecting_Faces_Using_ICCV_2017_paper.pdf", "https://ai.tencent.com/ailab/media/publications/Detecting_Faces_Using_Inside_Cascaded_Contextual_CNN.pdf"]}, {"id": "0e8760fc198a7e7c9f4193478c0e0700950a86cd", "title": "Brute-Force Facial Landmark Analysis With a 140, 000-Way Classifier", "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.01777.pdf"]}, {"id": "981449cdd5b820268c0876477419cba50d5d1316", "title": "Learning Deep Features for One-Class Classification", "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.05365.pdf"]}, {"id": "93dcea2419ca95b96a47e541748c46220d289d77", "title": "Multi-scale Fully Convolutional Network for Face Detection in the Wild", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Bai_Multi-Scale_Fully_Convolutional_CVPR_2017_paper.pdf"]}, {"id": "96faccdddef887673d6007fed8ff2574580cae1f", "title": "Multi-path Region-Based Convolutional Neural Network for Accurate Detection of Unconstrained \"Hard Faces\"", "year": "2017", "pdf": ["https://arxiv.org/pdf/1703.09145.pdf"]}, {"id": "405d9a71350c9a13adea41f9d7f7f9274793824f", "title": "Enhancing Interior and Exterior Deep Facial Features for Face Detection in the Wild", "year": "2018", "pdf": []}, {"id": "9797de286a3101fc31fb51995c18ec7d3eab804d", "title": "Modified Viola\u2013Jones algorithm with GPU accelerated training and parallelized skin color filtering-based face detection", "year": "2017", "pdf": []}, {"id": "7714a5aa27ab5ad4d06a81fbb3e973d3b1002ac1", "title": "SSD-Sface : Single shot multibox detector for small faces", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/7714/a5aa27ab5ad4d06a81fbb3e973d3b1002ac1.pdf"]}, {"id": "27da432cf2b9129dce256e5bf7f2f18953eef5a5", "title": "Face Recognition in Low Quality Images: A Survey", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.11519.pdf"]}, {"id": "aafeb3d76155ec28e8ab6b4d063105d5e04e471d", "title": "Reconstructing Intensity Images from Binary Spatial Gradient Cameras", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w4/papers/Jayasuriya_Reconstructing_Intensity_Images_CVPR_2017_paper.pdf", "http://www.andrew.cmu.edu/user/sjayasur/gradcam.pdf"]}, {"id": "032825000c03b8ab4c207e1af4daeb1f225eb025", "title": "A Novel Approach for Human Face Detection in Color Images Using Skin Color and Golden Ratio", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/0328/25000c03b8ab4c207e1af4daeb1f225eb025.pdf"]}, {"id": "581e920ddb6ecfc2a313a3aa6fed3d933b917ab0", "title": "Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/581e/920ddb6ecfc2a313a3aa6fed3d933b917ab0.pdf"]}, {"id": "15ebec3796a2e23d31c8c8ddf6d21555be6eadc6", "title": "Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks", "year": "2018", "pdf": ["https://arxiv.org/pdf/1809.03193.pdf"]}, {"id": "e065a2cb4534492ccf46d0afc81b9ad8b420c5ec", "title": "SFace: An Efficient Network for Face Detection in Large Scale Variations", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.06559.pdf"]}, {"id": "58bf72750a8f5100e0c01e55fd1b959b31e7dbce", "title": "PyramidBox: A Context-assisted Single Shot Face Detector", "year": "2018", "pdf": ["https://arxiv.org/pdf/1803.07737.pdf"]}, {"id": "2f16459e2e24dc91b3b4cac7c6294387d4a0eacf", "title": "Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining", "year": "2018", "pdf": ["http://poseidon.csd.auth.gr/papers/PUBLISHED/JOURNAL/pdf/2017/triantafyllidou_nousi_tefas_big_data_and_neural_networks.pdf"]}, {"id": "363e5a0e4cd857e98de72a726ad6f80cea9c50ab", "title": "Fast Landmark Localization With 3D Component Reconstruction and CNN for Cross-Pose Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1708.09580.pdf"]}, {"id": "95ea564bd983129ddb5535a6741e72bb1162c779", "title": "Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection", "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.00111.pdf"]}, {"id": "a7663528eb6c9b79a68b94800e30da952c0b6bb2", "title": "IFQ-Net : Integrated Fixed-point Quantization Networks for Embedded Vision", "year": "", "pdf": ["https://pdfs.semanticscholar.org/a766/3528eb6c9b79a68b94800e30da952c0b6bb2.pdf"]}, {"id": "17c0d99171efc957b88c31a465c59485ab033234", "title": "To learn image super-resolution, use a GAN to learn how to do image degradation first", "year": "2018", "pdf": ["https://arxiv.org/pdf/1807.11458.pdf"]}, {"id": "4209783b0cab1f22341f0600eed4512155b1dee6", "title": "Accurate and Efficient Similarity Search for Large Scale Face Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.00365.pdf"]}, {"id": "3352426a67eabe3516812cb66a77aeb8b4df4d1b", "title": "Joint Multi-view Face Alignment in the Wild", "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.06023.pdf"]}, {"id": "0c36c988acc9ec239953ff1b3931799af388ef70", "title": "Face Detection Using Improved Faster RCNN", "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.02142.pdf"]}, {"id": "c3a3f7758bccbead7c9713cb8517889ea6d04687", "title": "Funnel-structured cascade for multi-view face detection with alignment-awareness", "year": "2017", "pdf": ["https://arxiv.org/pdf/1609.07304.pdf"]}, {"id": "22264e60f1dfbc7d0b52549d1de560993dd96e46", "title": "UnitBox: An Advanced Object Detection Network", "year": "2016", "pdf": ["https://arxiv.org/pdf/1608.01471.pdf"]}, {"id": "e8b2a98f87b7b2593b4a046464c1ec63bfd13b51", "title": "CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection", "year": "2016", "pdf": ["https://arxiv.org/pdf/1606.05413.pdf"]}, {"id": "bdfcc45cfa495939789b73eec7e6e98a4d7e3f41", "title": "A Real-Time Face Detector Based on an End-to-End CNN", "year": "2017", "pdf": []}, {"id": "28cd46a078e8fad370b1aba34762a874374513a5", "title": "cvpaper.challenge in 2016: Futuristic Computer Vision through 1, 600 Papers Survey", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.06436.pdf"]}, {"id": "69de532d93ad8099f4d4902c4cad28db958adfea", "title": "Face Attention Network: An Effective Face Detector for the Occluded Faces", "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.07246.pdf"]}, {"id": "ff01bc3f49130d436fca24b987b7e3beedfa404d", "title": "Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face", "year": "2016", "pdf": ["http://www.mdpi.com/2073-8994/8/8/75/pdf"]}, {"id": "cf805d478aeb53520c0ab4fcdc9307d093c21e52", "title": "Finding Tiny Faces in the Wild with Generative Adversarial Network", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cf80/5d478aeb53520c0ab4fcdc9307d093c21e52.pdf"]}, {"id": "cb30c1370885033bc833bc7ef90a25ee0900c461", "title": "FaceOff: Anonymizing Videos in the Operating Rooms", "year": "2018", "pdf": ["https://arxiv.org/pdf/1808.04440.pdf"]}, {"id": "b1d89015f9b16515735d4140c84b0bacbbef19ac", "title": "Too Far to See? Not Really!\u2014Pedestrian Detection With Scale-Aware Localization Policy", "year": "2018", "pdf": ["https://arxiv.org/pdf/1709.00235.pdf"]}, {"id": "9a42c519f0aaa68debbe9df00b090ca446d25bc4", "title": "Face Recognition via Centralized Coordinate Learning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.05678.pdf"]}, {"id": "67484723e0c2cbeb936b2e863710385bdc7d5368", "title": "Anchor Cascade for Efficient Face Detection", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.03363.pdf"]}, {"id": "d689063294e217f1ec8b83fe4b60e706f1934787", "title": "Simultaneous Face Detection and Pose Estimation Using Convolutional Neural Network Cascade", "year": "2018", "pdf": []}, {"id": "56fd4c05869e11e4935d48aa1d7abb96072ac242", "title": "OpenFace 2.0: Facial Behavior Analysis Toolkit", "year": "2018", "pdf": []}, {"id": "8d4f0517eae232913bf27f516101a75da3249d15", "title": "Event-based Dynamic Face Detection and Tracking Based on Activity.", "year": "2018", "pdf": []}, {"id": "878301453e3d5cb1a1f7828002ea00f59cbeab06", "title": "Faceness-Net: Face Detection through Deep Facial Part Responses", "year": "2018", "pdf": ["https://arxiv.org/pdf/1701.08393.pdf"]}, {"id": "31b05f65405534a696a847dd19c621b7b8588263", "title": "UMDFaces: An annotated face dataset for training deep networks", "year": "2017", "pdf": ["https://arxiv.org/pdf/1611.01484.pdf"]}, {"id": "795aa8064b34c4bf4acdd8be3f1e5d06da5a7756", "title": "Face-MagNet: Magnifying Feature Maps to Detect Small Faces", "year": "2018", "pdf": ["https://arxiv.org/pdf/1803.05258.pdf"]}, {"id": "fb4c3b2f893baa1fbf8d16da2e09aa9868c61a7a", "title": "Decoupled Weight Decay Regularization", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/fb4c/3b2f893baa1fbf8d16da2e09aa9868c61a7a.pdf"]}, {"id": "31af1f2614823504d1d643d1b019c6f9d2150b15", "title": "Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs", "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.02765.pdf"]}, {"id": "d9c0310203179d5328c4f1475fa4d68c5f0c7324", "title": "Face Analysis in the Wild", "year": "2017", "pdf": []}, {"id": "9cc8cf0c7d7fa7607659921b6ff657e17e135ecc", "title": "Detecting Masked Faces in the Wild with LLE-CNNs", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017/papers/Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf"]}, {"id": "3a3e55cf5bfd689d6c922e082efa0cd71cd2ae5c", "title": "Face tracking with convolutional neural network heat-map", "year": "2018", "pdf": []}, {"id": "06bd34951305d9f36eb29cf4532b25272da0e677", "title": "A Fast and Accurate System for Face Detection, Identification, and Verification", "year": "2018", "pdf": ["https://arxiv.org/pdf/1809.07586.pdf"]}, {"id": "3a1c40eced07d59a3ea7acda94fa833c493909c1", "title": "AUMPNet: Simultaneous Action Units Detection and Intensity Estimation on Multipose Facial Images Using a Single Convolutional Neural Network", "year": "2017", "pdf": []}, {"id": "84a20d0a47c0d826b77f73075530d618ba7573d2", "title": "Look at Boundary: A Boundary-Aware Face Alignment Algorithm", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.10483.pdf"]}, {"id": "6be0ab66c31023762e26d309a4a9d0096f72a7f0", "title": "Enhance Visual Recognition under Adverse Conditions via Deep Networks", "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.07732.pdf"]}, {"id": "0cb2dd5f178e3a297a0c33068961018659d0f443", "title": "IARPA Janus Benchmark-B Face Dataset", "year": "2017", "pdf": ["http://biometrics.cse.msu.edu/Publications/Face/Whitelametal_IARPAJanusBenchmark-BFaceDataset_CVPRW17.pdf", "http://openaccess.thecvf.com/content_cvpr_2017_workshops/w6/papers/Whitelam_IARPA_Janus_Benchmark-B_CVPR_2017_paper.pdf", "http://www.vislab.ucr.edu/Biometrics2017/program_slides/Noblis_CVPRW_IJBB.pdf", "https://www.nist.gov/sites/default/files/documents/2017/05/30/readme.pdf"]}, {"id": "0341405252c80ff029a0d0065ca46d0ade943b03", "title": "A Coupled Encoder-Decoder Network for Joint Face Detection and Landmark Localization", "year": "2017", "pdf": []}, {"id": "6afe1f668eea8dfdd43f0780634073ed4545af23", "title": "Deep learning for content-based video retrieval in film and television production", "year": "2017", "pdf": []}, {"id": "ad75879082132a73fe173a890a0f414f2c279739", "title": "A comparison of CNN-based face and head detectors for real-time video surveillance applications", "year": "2017", "pdf": ["https://arxiv.org/pdf/1809.03336.pdf"]}, {"id": "24d376e4d580fb28fd66bc5e7681f1a8db3b6b78", "title": "Multi-Branch Fully Convolutional Network for Face Detection", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.06330.pdf"]}, {"id": "614a7c42aae8946c7ad4c36b53290860f6256441", "title": "Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks", "year": "2016", "pdf": ["https://arxiv.org/pdf/1604.02878.pdf"]}, {"id": "22f656d0f8426c84a33a267977f511f127bfd7f3", "title": "From Facial Expression Recognition to Interpersonal Relation Prediction", "year": "2017", "pdf": ["https://arxiv.org/pdf/1609.06426.pdf"]}, {"id": "26c89f890da91119ffa16d5a23fba963257ef3fc", "title": "Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1811.00218.pdf"]}, {"id": "7f5b379b12505d60f9303aab1fea48515d36d098", "title": "Performance Comparison of Deep Learning Techniques for Recognizing Birds in Aerial Images", "year": "2018", "pdf": []}, {"id": "84dcf04802743d9907b5b3ae28b19cbbacd97981", "title": "Face Detection using Deep Learning: An Improved Faster RCNN Approach", "year": "2018", "pdf": ["https://arxiv.org/pdf/1701.08289.pdf"]}, {"id": "5c3fd194ba96c5eea41c0772ad0b2292dedcd197", "title": "Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/5c3f/d194ba96c5eea41c0772ad0b2292dedcd197.pdf"]}, {"id": "793e7f1ba18848908da30cbad14323b0389fd2a8", "title": "End-to-End Face Detection and Cast Grouping in Movies Using Erd\u00f6s-R\u00e9nyi Clustering", "year": "2017", "pdf": ["https://arxiv.org/pdf/1709.02458.pdf"]}, {"id": "fd96432675911a702b8a4ce857b7c8619498bf9f", "title": "Improved Face Detection and Alignment using Cascade Deep Convolutional Network", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.09364.pdf"]}, {"id": "4d90d7834ae25ee6176c096d5d6608555766c0b1", "title": "Face and Body Association for Video-Based Face Recognition", "year": "2018", "pdf": []}, {"id": "c6ea6fee4823b511eecf41f6c2574a0728055baf", "title": "HoloFace: Augmenting Human-to-Human Interactions on HoloLens", "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.00278.pdf"]}, {"id": "0d760e7d762fa449737ad51431f3ff938d6803fe", "title": "LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems", "year": "2017", "pdf": ["https://arxiv.org/pdf/1705.05922.pdf"]}, {"id": "57178b36c21fd7f4529ac6748614bb3374714e91", "title": "IARPA Janus Benchmark - C: Face Dataset and Protocol", "year": "2018", "pdf": ["http://biometrics.cse.msu.edu/Publications/Face/Mazeetal_IARPAJanusBenchmarkCFaceDatasetAndProtocol_ICB2018.pdf"]}, {"id": "3f5b20c35f55417823f0201862d85af1f31e9348", "title": "Salience Biased Loss for Object Detection in Aerial Images", "year": "2018", "pdf": ["https://arxiv.org/pdf/1810.08103.pdf"]}]}
\ No newline at end of file +{"id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "citations": [{"id": "c9c9ade2ef4dffb7582a629a47ea70c31be7a35e", "title": "Detecting Faces Using Inside Cascaded Contextual CNN", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_Detecting_Faces_Using_ICCV_2017_paper.pdf", "https://ai.tencent.com/ailab/media/publications/Detecting_Faces_Using_Inside_Cascaded_Contextual_CNN.pdf"]}, {"id": "0e8760fc198a7e7c9f4193478c0e0700950a86cd", "title": "Brute-Force Facial Landmark Analysis With a 140, 000-Way Classifier", "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.01777.pdf"]}, {"id": "981449cdd5b820268c0876477419cba50d5d1316", "title": "Learning Deep Features for One-Class Classification", "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.05365.pdf"]}, {"id": "93dcea2419ca95b96a47e541748c46220d289d77", "title": "Multi-scale Fully Convolutional Network for Face Detection in the Wild", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Bai_Multi-Scale_Fully_Convolutional_CVPR_2017_paper.pdf"]}, {"id": "96faccdddef887673d6007fed8ff2574580cae1f", "title": "Multi-path Region-Based Convolutional Neural Network for Accurate Detection of Unconstrained \"Hard Faces\"", "year": "2017", "pdf": ["https://arxiv.org/pdf/1703.09145.pdf"]}, {"id": "405d9a71350c9a13adea41f9d7f7f9274793824f", "title": "Enhancing Interior and Exterior Deep Facial Features for Face Detection in the Wild", "year": "2018", "pdf": []}, {"id": "7714a5aa27ab5ad4d06a81fbb3e973d3b1002ac1", "title": "SSD-Sface : Single shot multibox detector for small faces", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/7714/a5aa27ab5ad4d06a81fbb3e973d3b1002ac1.pdf"]}, {"id": "27da432cf2b9129dce256e5bf7f2f18953eef5a5", "title": "Face Recognition in Low Quality Images: A Survey", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.11519.pdf"]}, {"id": "aafeb3d76155ec28e8ab6b4d063105d5e04e471d", "title": "Reconstructing Intensity Images from Binary Spatial Gradient Cameras", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w4/papers/Jayasuriya_Reconstructing_Intensity_Images_CVPR_2017_paper.pdf", "http://www.andrew.cmu.edu/user/sjayasur/gradcam.pdf"]}, {"id": "032825000c03b8ab4c207e1af4daeb1f225eb025", "title": "A Novel Approach for Human Face Detection in Color Images Using Skin Color and Golden Ratio", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/0328/25000c03b8ab4c207e1af4daeb1f225eb025.pdf"]}, {"id": "581e920ddb6ecfc2a313a3aa6fed3d933b917ab0", "title": "Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/581e/920ddb6ecfc2a313a3aa6fed3d933b917ab0.pdf"]}, {"id": "15ebec3796a2e23d31c8c8ddf6d21555be6eadc6", "title": "Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks", "year": "2018", "pdf": ["https://arxiv.org/pdf/1809.03193.pdf"]}, {"id": "e065a2cb4534492ccf46d0afc81b9ad8b420c5ec", "title": "SFace: An Efficient Network for Face Detection in Large Scale Variations", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.06559.pdf"]}, {"id": "58bf72750a8f5100e0c01e55fd1b959b31e7dbce", "title": "PyramidBox: A Context-assisted Single Shot Face Detector", "year": "2018", "pdf": ["https://arxiv.org/pdf/1803.07737.pdf"]}, {"id": "2f16459e2e24dc91b3b4cac7c6294387d4a0eacf", "title": "Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining", "year": "2018", "pdf": ["http://poseidon.csd.auth.gr/papers/PUBLISHED/JOURNAL/pdf/2017/triantafyllidou_nousi_tefas_big_data_and_neural_networks.pdf"]}, {"id": "363e5a0e4cd857e98de72a726ad6f80cea9c50ab", "title": "Fast Landmark Localization With 3D Component Reconstruction and CNN for Cross-Pose Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1708.09580.pdf"]}, {"id": "95ea564bd983129ddb5535a6741e72bb1162c779", "title": "Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection", "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.00111.pdf"]}, {"id": "a7663528eb6c9b79a68b94800e30da952c0b6bb2", "title": "IFQ-Net : Integrated Fixed-point Quantization Networks for Embedded Vision", "year": "", "pdf": ["https://pdfs.semanticscholar.org/a766/3528eb6c9b79a68b94800e30da952c0b6bb2.pdf"]}, {"id": "17c0d99171efc957b88c31a465c59485ab033234", "title": "To learn image super-resolution, use a GAN to learn how to do image degradation first", "year": "2018", "pdf": ["https://arxiv.org/pdf/1807.11458.pdf"]}, {"id": "4209783b0cab1f22341f0600eed4512155b1dee6", "title": "Accurate and Efficient Similarity Search for Large Scale Face Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.00365.pdf"]}, {"id": "c3a3f7758bccbead7c9713cb8517889ea6d04687", "title": "Funnel-structured cascade for multi-view face detection with alignment-awareness", "year": "2017", "pdf": ["https://arxiv.org/pdf/1609.07304.pdf"]}, {"id": "22264e60f1dfbc7d0b52549d1de560993dd96e46", "title": "UnitBox: An Advanced Object Detection Network", "year": "2016", "pdf": ["https://arxiv.org/pdf/1608.01471.pdf"]}, {"id": "bdfcc45cfa495939789b73eec7e6e98a4d7e3f41", "title": "A Real-Time Face Detector Based on an End-to-End CNN", "year": "2017", "pdf": []}, {"id": "28cd46a078e8fad370b1aba34762a874374513a5", "title": "cvpaper.challenge in 2016: Futuristic Computer Vision through 1, 600 Papers Survey", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.06436.pdf"]}, {"id": "69de532d93ad8099f4d4902c4cad28db958adfea", "title": "Face Attention Network: An Effective Face Detector for the Occluded Faces", "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.07246.pdf"]}, {"id": "ff01bc3f49130d436fca24b987b7e3beedfa404d", "title": "Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face", "year": "2016", "pdf": ["http://www.mdpi.com/2073-8994/8/8/75/pdf"]}, {"id": "cf805d478aeb53520c0ab4fcdc9307d093c21e52", "title": "Finding Tiny Faces in the Wild with Generative Adversarial Network", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cf80/5d478aeb53520c0ab4fcdc9307d093c21e52.pdf"]}, {"id": "cb30c1370885033bc833bc7ef90a25ee0900c461", "title": "FaceOff: Anonymizing Videos in the Operating Rooms", "year": "2018", "pdf": ["https://arxiv.org/pdf/1808.04440.pdf"]}, {"id": "b1d89015f9b16515735d4140c84b0bacbbef19ac", "title": "Too Far to See? Not Really!\u2014Pedestrian Detection With Scale-Aware Localization Policy", "year": "2018", "pdf": ["https://arxiv.org/pdf/1709.00235.pdf"]}, {"id": "9a42c519f0aaa68debbe9df00b090ca446d25bc4", "title": "Face Recognition via Centralized Coordinate Learning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.05678.pdf"]}, {"id": "67484723e0c2cbeb936b2e863710385bdc7d5368", "title": "Anchor Cascade for Efficient Face Detection", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.03363.pdf"]}, {"id": "d689063294e217f1ec8b83fe4b60e706f1934787", "title": "Simultaneous Face Detection and Pose Estimation Using Convolutional Neural Network Cascade", "year": "2018", "pdf": []}, {"id": "56fd4c05869e11e4935d48aa1d7abb96072ac242", "title": "OpenFace 2.0: Facial Behavior Analysis Toolkit", "year": "2018", "pdf": []}, {"id": "8d4f0517eae232913bf27f516101a75da3249d15", "title": "Event-based Dynamic Face Detection and Tracking Based on Activity.", "year": "2018", "pdf": []}, {"id": "878301453e3d5cb1a1f7828002ea00f59cbeab06", "title": "Faceness-Net: Face Detection through Deep Facial Part Responses", "year": "2018", "pdf": ["https://arxiv.org/pdf/1701.08393.pdf"]}, {"id": "31b05f65405534a696a847dd19c621b7b8588263", "title": "UMDFaces: An annotated face dataset for training deep networks", "year": "2017", "pdf": ["https://arxiv.org/pdf/1611.01484.pdf"]}, {"id": "795aa8064b34c4bf4acdd8be3f1e5d06da5a7756", "title": "Face-MagNet: Magnifying Feature Maps to Detect Small Faces", "year": "2018", "pdf": ["https://arxiv.org/pdf/1803.05258.pdf"]}, {"id": "fb4c3b2f893baa1fbf8d16da2e09aa9868c61a7a", "title": "Decoupled Weight Decay Regularization", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/fb4c/3b2f893baa1fbf8d16da2e09aa9868c61a7a.pdf"]}, {"id": "31af1f2614823504d1d643d1b019c6f9d2150b15", "title": "Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs", "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.02765.pdf"]}, {"id": "d9c0310203179d5328c4f1475fa4d68c5f0c7324", "title": "Face Analysis in the Wild", "year": "2017", "pdf": []}, {"id": "9cc8cf0c7d7fa7607659921b6ff657e17e135ecc", "title": "Detecting Masked Faces in the Wild with LLE-CNNs", "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017/papers/Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf"]}, {"id": "06bd34951305d9f36eb29cf4532b25272da0e677", "title": "A Fast and Accurate System for Face Detection, Identification, and Verification", "year": "2018", "pdf": ["https://arxiv.org/pdf/1809.07586.pdf"]}, {"id": "3a1c40eced07d59a3ea7acda94fa833c493909c1", "title": "AUMPNet: Simultaneous Action Units Detection and Intensity Estimation on Multipose Facial Images Using a Single Convolutional Neural Network", "year": "2017", "pdf": []}, {"id": "84a20d0a47c0d826b77f73075530d618ba7573d2", "title": "Look at Boundary: A Boundary-Aware Face Alignment Algorithm", "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.10483.pdf"]}, {"id": "0cb2dd5f178e3a297a0c33068961018659d0f443", "title": "IARPA Janus Benchmark-B Face Dataset", "year": "2017", "pdf": ["http://biometrics.cse.msu.edu/Publications/Face/Whitelametal_IARPAJanusBenchmark-BFaceDataset_CVPRW17.pdf", "http://openaccess.thecvf.com/content_cvpr_2017_workshops/w6/papers/Whitelam_IARPA_Janus_Benchmark-B_CVPR_2017_paper.pdf", "http://www.vislab.ucr.edu/Biometrics2017/program_slides/Noblis_CVPRW_IJBB.pdf", "https://www.nist.gov/sites/default/files/documents/2017/05/30/readme.pdf"]}, {"id": "0341405252c80ff029a0d0065ca46d0ade943b03", "title": "A Coupled Encoder-Decoder Network for Joint Face Detection and Landmark Localization", "year": "2017", "pdf": []}, {"id": "ad75879082132a73fe173a890a0f414f2c279739", "title": "A comparison of CNN-based face and head detectors for real-time video surveillance applications", "year": "2017", "pdf": ["https://arxiv.org/pdf/1809.03336.pdf"]}, {"id": "24d376e4d580fb28fd66bc5e7681f1a8db3b6b78", "title": "Multi-Branch Fully Convolutional Network for Face Detection", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.06330.pdf"]}, {"id": "614a7c42aae8946c7ad4c36b53290860f6256441", "title": "Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks", "year": "2016", "pdf": ["https://arxiv.org/pdf/1604.02878.pdf"]}, {"id": "22f656d0f8426c84a33a267977f511f127bfd7f3", "title": "From Facial Expression Recognition to Interpersonal Relation Prediction", "year": "2017", "pdf": ["https://arxiv.org/pdf/1609.06426.pdf"]}, {"id": "7f5b379b12505d60f9303aab1fea48515d36d098", "title": "Performance Comparison of Deep Learning Techniques for Recognizing Birds in Aerial Images", "year": "2018", "pdf": []}, {"id": "84dcf04802743d9907b5b3ae28b19cbbacd97981", "title": "Face Detection using Deep Learning: An Improved Faster RCNN Approach", "year": "2018", "pdf": ["https://arxiv.org/pdf/1701.08289.pdf"]}, {"id": "5c3fd194ba96c5eea41c0772ad0b2292dedcd197", "title": "Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm", "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/5c3f/d194ba96c5eea41c0772ad0b2292dedcd197.pdf"]}, {"id": "793e7f1ba18848908da30cbad14323b0389fd2a8", "title": "End-to-End Face Detection and Cast Grouping in Movies Using Erd\u00f6s-R\u00e9nyi Clustering", "year": "2017", "pdf": ["https://arxiv.org/pdf/1709.02458.pdf"]}, {"id": "fd96432675911a702b8a4ce857b7c8619498bf9f", "title": "Improved Face Detection and Alignment using Cascade Deep Convolutional Network", "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.09364.pdf"]}, {"id": "4d90d7834ae25ee6176c096d5d6608555766c0b1", "title": "Face and Body Association for Video-Based Face Recognition", "year": "2018", "pdf": []}, {"id": "c6ea6fee4823b511eecf41f6c2574a0728055baf", "title": "HoloFace: Augmenting Human-to-Human Interactions on HoloLens", "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.00278.pdf"]}, {"id": "0d760e7d762fa449737ad51431f3ff938d6803fe", "title": "LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems", "year": "2017", "pdf": ["https://arxiv.org/pdf/1705.05922.pdf"]}, {"id": "57178b36c21fd7f4529ac6748614bb3374714e91", "title": "IARPA Janus Benchmark - C: Face Dataset and Protocol", "year": "2018", "pdf": ["http://biometrics.cse.msu.edu/Publications/Face/Mazeetal_IARPAJanusBenchmarkCFaceDatasetAndProtocol_ICB2018.pdf"]}, {"id": "3f5b20c35f55417823f0201862d85af1f31e9348", "title": "Salience Biased Loss for Object Detection in Aerial Images", "year": "2018", "pdf": ["https://arxiv.org/pdf/1810.08103.pdf"]}]}
\ No newline at end of file |