diff options
Diffstat (limited to 'site/datasets/unknown/vgg_faces2.json')
| -rw-r--r-- | site/datasets/unknown/vgg_faces2.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/unknown/vgg_faces2.json b/site/datasets/unknown/vgg_faces2.json index 753e7f63..311ff25e 100644 --- a/site/datasets/unknown/vgg_faces2.json +++ b/site/datasets/unknown/vgg_faces2.json @@ -1 +1 @@ -{"id": "eb027969f9310e0ae941e2adee2d42cdf07d938c", "paper": {"paper_id": "eb027969f9310e0ae941e2adee2d42cdf07d938c", "key": "vgg_faces2", "title": "VGGFace2: A Dataset for Recognising Faces across Pose and Age", "year": "2018", "pdf": "https://arxiv.org/pdf/1710.08092.pdf", "address": "", "name": "VGG Face2"}, "citations": [{"id": "c6eb026d3a0081f4cb5cde16d3170f8ecf8ce706", "title": "Face Recognition: From Traditional to Deep Learning Methods", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.00116.pdf"}, {"id": "266766818dbc5a4ca1161ae2bc14c9e269ddc490", "title": "Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/2667/66818dbc5a4ca1161ae2bc14c9e269ddc490.pdf"}, {"id": "8199803f476c12c7f6c0124d55d156b5d91314b6", "title": "The iNaturalist Species Classification and Detection Dataset", "year": "2017", "pdf": "https://arxiv.org/pdf/1707.06642.pdf"}, {"id": "a2344004f0e1409c0c9473d071a5cfd74bff0a5d", "title": "Learnable PINs: Cross-modal Embeddings for Person Identity", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.00833.pdf"}, {"id": "1dd3faf5488751c9de10977528ab96be24616138", "title": "Detecting Anomalous Faces with 'No Peeking' Autoencoders", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/1dd3/faf5488751c9de10977528ab96be24616138.pdf"}, {"id": "9a42c519f0aaa68debbe9df00b090ca446d25bc4", "title": "Face Recognition via Centralized Coordinate Learning", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/9a42/c519f0aaa68debbe9df00b090ca446d25bc4.pdf"}, {"id": "f616c433671302eff23923d38ea87223202818f6", "title": "Model-Reuse Attacks on Deep Learning Systems", "year": "2018", "pdf": "http://dl.acm.org/citation.cfm?id=3243757"}, {"id": "e6b45d5a86092bbfdcd6c3c54cda3d6c3ac6b227", "title": "Pairwise Relational Networks for Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1808.04976.pdf"}, {"id": "85860d38c66a5cf2e6ffd6475a3a2ba096ea2920", "title": "Celeb-500K: A Large Training Dataset for Face Recognition", "year": "2018", "pdf": "http://doi.org/10.1109/ICIP.2018.8451704"}, {"id": "5c315aae464602115674716a7f976c4992fcb98e", "title": "Teachers\u2019 Perception in the Classroom", "year": "", "pdf": "https://pdfs.semanticscholar.org/5c31/5aae464602115674716a7f976c4992fcb98e.pdf"}, {"id": "4b48e912a17c79ac95d6a60afed8238c9ab9e553", "title": "Minimum Margin Loss for Deep Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.06741.pdf"}, {"id": "692aecba13add2b8c1d82db303f5b2ec743ceb44", "title": "FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/692a/ecba13add2b8c1d82db303f5b2ec743ceb44.pdf"}, {"id": "9ebe5d78163a91239f10c453d76082dfa329851d", "title": "Teacher's Perception in the Classroom", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.08897.pdf"}, {"id": "be72b20247fb4dc4072d962ced77ed89aa40372f", "title": "Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.07718.pdf"}, {"id": "bc15e0ebe7ff84e090aa2d74d753d87906d497f7", "title": "The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments", "year": "2018", "pdf": "https://arxiv.org/pdf/1808.10032.pdf"}, {"id": "069bb452e015ef53f0ef30e9690e460ccc73cf03", "title": "Multicolumn Networks for Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.09192.pdf"}, {"id": "040dc119d5ca9ea3d5fc39953a91ec507ed8cc5d", "title": "Large-scale Bisample Learning on ID vs. Spot Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1806.03018.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": "fbc2f5cf943f440b1ba2374ecf82d0176a44f1eb", "title": "3D-Aided Dual-Agent GANs for Unconstrained Face Recognition.", "year": "2018", "pdf": "https://www.ncbi.nlm.nih.gov/pubmed/30040629"}, {"id": "361eaef45fccfffd5b7df12fba902490a7d24a8d", "title": "Robust deep learning features for face recognition under mismatched conditions", "year": "2018", "pdf": "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8404319"}, {"id": "39ed31ced75e6151dde41944a47b4bdf324f922b", "title": "Pose-Guided Photorealistic Face Rotation", "year": "", "pdf": "https://pdfs.semanticscholar.org/39ed/31ced75e6151dde41944a47b4bdf324f922b.pdf"}, {"id": "e4a1b46b5c639d433d21b34b788df8d81b518729", "title": "Side Information for Face Completion: a Robust PCA Approach", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/e4a1/b46b5c639d433d21b34b788df8d81b518729.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": "12ba7c6f559a69fbfaacf61bfb2f8431505b09a0", "title": "DocFace+: ID Document to Selfie Matching", "year": "2018", "pdf": "https://arxiv.org/pdf/1809.05620.pdf"}, {"id": "cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce", "title": "Git Loss for Deep Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.08512.pdf"}, {"id": "48fb35946641351f7480a5b88567aae59e526d82", "title": "Generating faces for affect analysis", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.05027.pdf"}, {"id": "c866a2afc871910e3282fd9498dce4ab20f6a332", "title": "Surveillance Face Recognition Challenge", "year": "2018", "pdf": "https://arxiv.org/pdf/1804.09691.pdf"}, {"id": "cf4e5206722ba16061982b885f8c7c86beacd27c", "title": "Group-Level Emotion Recognition Using Hybrid Deep Models Based on Faces, Scenes, Skeletons and Visual Attentions", "year": "2018", "pdf": "http://dl.acm.org/citation.cfm?id=3264990"}, {"id": "2edf55ebc88e89c4caff0c49c6b8e79f46407d19", "title": "Pruning Deep Neural Networks using Partial Least Squares", "year": "2018", "pdf": "https://arxiv.org/pdf/1810.07610.pdf"}, {"id": "173657da03e3249f4e47457d360ab83b3cefbe63", "title": "HKU-Face : A Large Scale Dataset for Deep Face Recognition Final Report", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/1736/57da03e3249f4e47457d360ab83b3cefbe63.pdf"}, {"id": "ac5ab8f71edde6d1a2129da12d051ed03a8446a1", "title": "Comparator Networks", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.11440.pdf"}, {"id": "5e39deb4bff7b887c8f3a44dfe1352fbcde8a0bd", "title": "Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!", "year": "2018", "pdf": "https://arxiv.org/pdf/1810.06221.pdf"}, {"id": "59fc69b3bc4759eef1347161e1248e886702f8f7", "title": "Final Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/59fc/69b3bc4759eef1347161e1248e886702f8f7.pdf"}, {"id": "94f74c6314ffd02db581e8e887b5fd81ce288dbf", "title": "A Light CNN for Deep Face Representation with Noisy Labels", "year": 2015, "pdf": "http://pdfs.semanticscholar.org/94f7/4c6314ffd02db581e8e887b5fd81ce288dbf.pdf"}, {"id": "832a9584e85af1675d49ee35fd13283b21ce3a3f", "title": "Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.00112.pdf"}, {"id": "b7ec41005ce4384e76e3be854ecccd564d2f89fb", "title": "Granular Computing and Sequential Analysis of Deep Embeddings in Fast Still-to-Video Face Recognition", "year": "2018", "pdf": "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8441009"}]}
\ No newline at end of file +{"id": "eb027969f9310e0ae941e2adee2d42cdf07d938c", "citations": [{"id": "c6eb026d3a0081f4cb5cde16d3170f8ecf8ce706", "title": "Face Recognition: From Traditional to Deep Learning Methods", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.00116.pdf"}, {"id": "266766818dbc5a4ca1161ae2bc14c9e269ddc490", "title": "Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/2667/66818dbc5a4ca1161ae2bc14c9e269ddc490.pdf"}, {"id": "8199803f476c12c7f6c0124d55d156b5d91314b6", "title": "The iNaturalist Species Classification and Detection Dataset", "year": "2017", "pdf": "https://arxiv.org/pdf/1707.06642.pdf"}, {"id": "a2344004f0e1409c0c9473d071a5cfd74bff0a5d", "title": "Learnable PINs: Cross-modal Embeddings for Person Identity", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.00833.pdf"}, {"id": "1dd3faf5488751c9de10977528ab96be24616138", "title": "Detecting Anomalous Faces with 'No Peeking' Autoencoders", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/1dd3/faf5488751c9de10977528ab96be24616138.pdf"}, {"id": "9a42c519f0aaa68debbe9df00b090ca446d25bc4", "title": "Face Recognition via Centralized Coordinate Learning", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/9a42/c519f0aaa68debbe9df00b090ca446d25bc4.pdf"}, {"id": "f616c433671302eff23923d38ea87223202818f6", "title": "Model-Reuse Attacks on Deep Learning Systems", "year": "2018", "pdf": "http://dl.acm.org/citation.cfm?id=3243757"}, {"id": "e6b45d5a86092bbfdcd6c3c54cda3d6c3ac6b227", "title": "Pairwise Relational Networks for Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1808.04976.pdf"}, {"id": "85860d38c66a5cf2e6ffd6475a3a2ba096ea2920", "title": "Celeb-500K: A Large Training Dataset for Face Recognition", "year": "2018", "pdf": "http://doi.org/10.1109/ICIP.2018.8451704"}, {"id": "5c315aae464602115674716a7f976c4992fcb98e", "title": "Teachers\u2019 Perception in the Classroom", "year": "", "pdf": "https://pdfs.semanticscholar.org/5c31/5aae464602115674716a7f976c4992fcb98e.pdf"}, {"id": "4b48e912a17c79ac95d6a60afed8238c9ab9e553", "title": "Minimum Margin Loss for Deep Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.06741.pdf"}, {"id": "692aecba13add2b8c1d82db303f5b2ec743ceb44", "title": "FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/692a/ecba13add2b8c1d82db303f5b2ec743ceb44.pdf"}, {"id": "9ebe5d78163a91239f10c453d76082dfa329851d", "title": "Teacher's Perception in the Classroom", "year": "2018", "pdf": "https://arxiv.org/pdf/1805.08897.pdf"}, {"id": "be72b20247fb4dc4072d962ced77ed89aa40372f", "title": "Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.07718.pdf"}, {"id": "bc15e0ebe7ff84e090aa2d74d753d87906d497f7", "title": "The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments", "year": "2018", "pdf": "https://arxiv.org/pdf/1808.10032.pdf"}, {"id": "069bb452e015ef53f0ef30e9690e460ccc73cf03", "title": "Multicolumn Networks for Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.09192.pdf"}, {"id": "040dc119d5ca9ea3d5fc39953a91ec507ed8cc5d", "title": "Large-scale Bisample Learning on ID vs. Spot Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1806.03018.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": "fbc2f5cf943f440b1ba2374ecf82d0176a44f1eb", "title": "3D-Aided Dual-Agent GANs for Unconstrained Face Recognition.", "year": "2018", "pdf": "https://www.ncbi.nlm.nih.gov/pubmed/30040629"}, {"id": "361eaef45fccfffd5b7df12fba902490a7d24a8d", "title": "Robust deep learning features for face recognition under mismatched conditions", "year": "2018", "pdf": "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8404319"}, {"id": "39ed31ced75e6151dde41944a47b4bdf324f922b", "title": "Pose-Guided Photorealistic Face Rotation", "year": "", "pdf": "https://pdfs.semanticscholar.org/39ed/31ced75e6151dde41944a47b4bdf324f922b.pdf"}, {"id": "e4a1b46b5c639d433d21b34b788df8d81b518729", "title": "Side Information for Face Completion: a Robust PCA Approach", "year": 2018, "pdf": "http://pdfs.semanticscholar.org/e4a1/b46b5c639d433d21b34b788df8d81b518729.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": "12ba7c6f559a69fbfaacf61bfb2f8431505b09a0", "title": "DocFace+: ID Document to Selfie Matching", "year": "2018", "pdf": "https://arxiv.org/pdf/1809.05620.pdf"}, {"id": "cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce", "title": "Git Loss for Deep Face Recognition", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.08512.pdf"}, {"id": "48fb35946641351f7480a5b88567aae59e526d82", "title": "Generating faces for affect analysis", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.05027.pdf"}, {"id": "c866a2afc871910e3282fd9498dce4ab20f6a332", "title": "Surveillance Face Recognition Challenge", "year": "2018", "pdf": "https://arxiv.org/pdf/1804.09691.pdf"}, {"id": "cf4e5206722ba16061982b885f8c7c86beacd27c", "title": "Group-Level Emotion Recognition Using Hybrid Deep Models Based on Faces, Scenes, Skeletons and Visual Attentions", "year": "2018", "pdf": "http://dl.acm.org/citation.cfm?id=3264990"}, {"id": "2edf55ebc88e89c4caff0c49c6b8e79f46407d19", "title": "Pruning Deep Neural Networks using Partial Least Squares", "year": "2018", "pdf": "https://arxiv.org/pdf/1810.07610.pdf"}, {"id": "173657da03e3249f4e47457d360ab83b3cefbe63", "title": "HKU-Face : A Large Scale Dataset for Deep Face Recognition Final Report", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/1736/57da03e3249f4e47457d360ab83b3cefbe63.pdf"}, {"id": "ac5ab8f71edde6d1a2129da12d051ed03a8446a1", "title": "Comparator Networks", "year": "2018", "pdf": "https://arxiv.org/pdf/1807.11440.pdf"}, {"id": "5e39deb4bff7b887c8f3a44dfe1352fbcde8a0bd", "title": "Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!", "year": "2018", "pdf": "https://arxiv.org/pdf/1810.06221.pdf"}, {"id": "59fc69b3bc4759eef1347161e1248e886702f8f7", "title": "Final Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition", "year": "2018", "pdf": "https://pdfs.semanticscholar.org/59fc/69b3bc4759eef1347161e1248e886702f8f7.pdf"}, {"id": "94f74c6314ffd02db581e8e887b5fd81ce288dbf", "title": "A Light CNN for Deep Face Representation with Noisy Labels", "year": 2015, "pdf": "http://pdfs.semanticscholar.org/94f7/4c6314ffd02db581e8e887b5fd81ce288dbf.pdf"}, {"id": "832a9584e85af1675d49ee35fd13283b21ce3a3f", "title": "Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy", "year": "2018", "pdf": "https://arxiv.org/pdf/1811.00112.pdf"}, {"id": "b7ec41005ce4384e76e3be854ecccd564d2f89fb", "title": "Granular Computing and Sequential Analysis of Deep Embeddings in Fast Still-to-Video Face Recognition", "year": "2018", "pdf": "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8441009"}]}
\ No newline at end of file |