summaryrefslogtreecommitdiff
path: root/site/datasets/final/wider_face.json
diff options
context:
space:
mode:
Diffstat (limited to 'site/datasets/final/wider_face.json')
-rw-r--r--site/datasets/final/wider_face.json2
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/final/wider_face.json b/site/datasets/final/wider_face.json
index 3d13bbe5..d2ff10b9 100644
--- a/site/datasets/final/wider_face.json
+++ b/site/datasets/final/wider_face.json
@@ -1 +1 @@
-{"id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "dataset": {"key": "wider_face", "name_short": "WIDER FACE", "using": "N", "ft_share": "1", "subset_of": "", "superset_of": "", "name_full": "Web Image Dataset for Event Recognition Face", "url": "http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/", "added_on": "", "faces": "", "pdf_paper": "Y", "comments": "data drom WIDER dataset", "": "", "relevance": ""}, "statistics": {"key": "wider_face", "name": "WIDER FACE", "berit": "Y", "charlie": "", "adam": "", "priority": "N", "wild": "Y", "indoor": "", "outdoor": "", "cyberspace": "Y", "names": "", "downloaded": "N", "year_start": "", "year_end": "", "year_published": "2016", "ongoing": "", "images": "32,203 ", "videos": "", "faces_unique": "0 ", "total_faces": "", "img_per_person": "", "num_cameras": "", "faces_persons": "393,703 ", "female": "", "male": "", "landmarks": "", "width": "", "height": "", "color": "", "gray": "", "derivative_of": "Y", "tags": "", "source": "wider", "purpose_short": "face detection benchmark dataset", "size_gb": "", "agreement": "NA", "agree_requied": "", "agreement_signed": "", "comment": "", "comment 2": "", "comment 3": "", "": ""}, "paper": {"paper_id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "key": "wider_face", "title": "WIDER FACE: A Face Detection Benchmark", "year": "2016", "pdf": ["https://arxiv.org/pdf/1511.06523.pdf"], "address": "", "name": "WIDER FACE", "doi": []}, "address": null, "additional_papers": [], "citations": [{"id": "28646c6220848db46c6944967298d89a6559c700", "title": "It takes two to tango : Cascading off-the-shelf face detectors", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2018", "pdf": "https://pdfs.semanticscholar.org/2864/6c6220848db46c6944967298d89a6559c700.pdf"}, {"id": "def2983576001bac7d6461d78451159800938112", "title": "The Do\u2019s and Don\u2019ts for CNN-Based Face Verification", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1705.07426.pdf"}, {"id": "2d8001ffee6584b3f4d951d230dc00a06e8219f8", "title": "Feature Agglomeration Networks for Single Stage Face Detection", "addresses": [{"address": "Singapore Management University", "lat": "1.29500195", "lng": "103.84909214", "type": "edu"}, {"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1712.00721.pdf"}, {"id": "d8fbd3a16d2e2e59ce0cff98b3fd586863878dc1", "title": "Face detection and recognition for home service robots with end-to-end deep neural networks", "addresses": [{"address": "Futurewei Technologies Inc., Santa Clara, CA", "lat": "37.37344400", "lng": "-121.96487270", "type": "company"}], "year": "2017", "pdf": "http://mirlab.org/conference_papers/International_Conference/ICASSP%202017/pdfs/0002232.pdf"}, {"id": "e8523c4ac9d7aa21f3eb4062e09f2a3bc1eedcf7", "title": "Toward End-to-End Face Recognition Through Alignment Learning", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1701.07174.pdf"}, {"id": "4e30107ee6a2e087f14a7725e7fc5535ec2f5a5f", "title": "\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u043d\u043e\u0432\u043e\u0441\u0442\u043d\u044b\u0445 \u0441\u044e\u0436\u0435\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0441\u043e\u0431\u044b\u0442\u0438\u0439\u043d\u044b\u0445 \u0444\u043e\u0442\u043e\u0433\u0440\u0430\u0444\u0438\u0439 (News Stories Representation Using Event Photos)", "addresses": [{"address": "Lomonosov Moscow State University", "lat": "55.70229715", "lng": "37.53179777", "type": "edu"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/4e30/107ee6a2e087f14a7725e7fc5535ec2f5a5f.pdf"}, {"id": "72cbbdee4f6eeee8b7dd22cea6092c532271009f", "title": "Masquer Hunter: Adversarial Occlusion-aware Face Detection", "addresses": [{"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1709.05188.pdf"}, {"id": "bd236913cfe07896e171ece9bda62c18b8c8197e", "title": "Deep Learning with Energy-efficient Binary Gradient Cameras", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2016", "pdf": "https://arxiv.org/pdf/1612.00986.pdf"}, {"id": "e659221538d256b2c3e0724deff749eda903fc7d", "title": "Fine-Grained Head Pose Estimation Without Keypoints", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1710.00925.pdf"}, {"id": "acee2201f8a15990551804dd382b86973eb7c0a8", "title": "To boost or not to boost? On the limits of boosted trees for object detection", "addresses": [{"address": "University of California, San Diego", "lat": "32.87935255", "lng": "-117.23110049", "type": "edu"}], "year": "2016", "pdf": "https://arxiv.org/pdf/1701.01692.pdf"}, {"id": "377f2b65e6a9300448bdccf678cde59449ecd337", "title": "Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results", "addresses": [{"address": "Johns Hopkins University", "lat": "39.32905300", "lng": "-76.61942500", "type": "edu"}, {"address": "Rutgers University", "lat": "40.47913175", "lng": "-74.43168868", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1804.10275.pdf"}, {"id": "6dbdb07ce2991db0f64c785ad31196dfd4dae721", "title": "Seeing Small Faces from Robust Anchor's Perspective", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1802.09058.pdf"}, {"id": "aa799d721f75510be236ac73f26ec92b0a89ab10", "title": "Computer Vision \u2013 ECCV 2018", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "f79e4ba09402adab54d2efadd1c4bfe4e20c5da5", "title": "A highly accurate facial region network for unconstrained face detection", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "3c97c32ff575989ef2869f86d89c63005fc11ba9", "title": "Face Detection with the Faster R-CNN", "addresses": [{"address": "University of Massachusetts", "lat": "42.38897850", "lng": "-72.52869870", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1606.03473.pdf"}, {"id": "25c108a56e4cb757b62911639a40e9caf07f1b4f", "title": "Recurrent Scale Approximation for Object Detection in CNN", "addresses": [{"address": "SenseTime", "lat": "39.99300800", "lng": "116.32988200", "type": "company"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1707.09531.pdf"}, {"id": "24d45df91ebcfac7a49cdfb7116e971e12880612", "title": "UNICITY: A depth maps database for people detection in security airlocks", "addresses": [{"address": "IDIAP Research Institute", "lat": "46.10923700", "lng": "7.08453549", "type": "edu"}], "year": "2018", "pdf": "https://pdfs.semanticscholar.org/24d4/5df91ebcfac7a49cdfb7116e971e12880612.pdf"}, {"id": "7788fa76f1488b1597ee2bebc462f628e659f61e", "title": "A Privacy-Aware Architecture at the Edge for Autonomous Real-Time Identity Reidentification in Crowds", "addresses": [{"address": "University of Texas at San Antonio", "lat": "29.58333105", "lng": "-98.61944505", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "e4e07f5f201c6986e93ddb42dcf11a43c339ea2e", "title": "Cross-pose landmark localization using multi-dropout framework", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "11824658170994e4d4655e8f688bace16a0d3e48", "title": "Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Framework", "addresses": [{"address": "Qatar University", "lat": "25.37461295", "lng": "51.48980354", "type": "edu"}, {"address": "University of Warwick", "lat": "52.37931310", "lng": "-1.56042520", "type": "edu"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/1182/4658170994e4d4655e8f688bace16a0d3e48.pdf"}, {"id": "beb49072f5ba79ed24750108c593e8982715498e", "title": "GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data", "addresses": [{"address": "Peking University", "lat": "39.99223790", "lng": "116.30393816", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1705.04932.pdf"}, {"id": "15ee80e86e75bf1413dc38f521b9142b28fe02d1", "title": "Towards a deep learning framework for unconstrained face detection", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2016", "pdf": "https://arxiv.org/pdf/1612.05322.pdf"}, {"id": "cd023d2d067365c83d8e27431e83e7e66082f718", "title": "Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1804.06039.pdf"}, {"id": "438e7999c937b94f0f6384dbeaa3febff6d283b6", "title": "Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild", "addresses": [{"address": "University of Surrey", "lat": "51.24303255", "lng": "-0.59001382", "type": "edu"}, {"address": "Jiangnan University", "lat": "31.48542550", "lng": "120.27395810", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1705.02402.pdf"}, {"id": "35ccc836df60cd99c731412fe44156c7fd057b99", "title": "A cascade framework for masked face detection", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "Shanghai University", "lat": "31.32235655", "lng": "121.38400941", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "ac6c3b3e92ff5fbcd8f7967696c7aae134bea209", "title": "Deep Cascaded Bi-Network for Face Hallucination", "addresses": [{"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}, {"address": "Shenzhen Institutes of Advanced Technology", "lat": "22.59805605", "lng": "113.98533784", "type": "edu"}, {"address": "University of California, Merced", "lat": "37.36566745", "lng": "-120.42158888", "type": "edu"}], "year": "2016", "pdf": "https://arxiv.org/pdf/1607.05046.pdf"}, {"id": "4203f10b41e7931a63598989aa14478c04b725c9", "title": "Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1712.08263.pdf"}, {"id": "cc70fb1ab585378c79a2ab94776723e597afe379", "title": "Detect face in the wild using CNN cascade with feature aggregation at multi-resolution", "addresses": [{"address": "Swansea University", "lat": "51.60915780", "lng": "-3.97934429", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "a896ddeb0d253739c9aaef7fc1f170a2ba8407d3", "title": "SSH: Single Stage Headless Face Detector", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1708.03979.pdf"}, {"id": "eb87151fd2796ff5b4bbcf1906d41d53ac6c5595", "title": "Enhanced face detection using body part detections for wearable cameras", "addresses": [{"address": "IBM Thomas J. Watson Research Center", "lat": "41.21002475", "lng": "-73.80407056", "type": "company"}], "year": "2016", "pdf": null}, {"id": "185263189a30986e31566394680d6d16b0089772", "title": "Efficient Annotation of Objects for Video Analysis", "addresses": [{"address": "International Institute of Information Technology", "lat": "17.44549570", "lng": "78.34854698", "type": "edu"}], "year": "2018", "pdf": "https://pdfs.semanticscholar.org/1852/63189a30986e31566394680d6d16b0089772.pdf"}, {"id": "19d4b3679294563247c126148912d44cbf03e40e", "title": "Value-Aware Resampling and Loss for Imbalanced Classification", "addresses": [{"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "853fc1794892175e2318f55785ca8e2ce6fd7537", "title": "FHEDN: A context modeling Feature Hierarchy Encoder-Decoder Network for face detection", "addresses": [{"address": "Chongqing University", "lat": "29.50841740", "lng": "106.57858552", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "ede5982980aa76deae8f9dc5143a724299d67742", "title": "Lightweight two-stream convolutional face detection", "addresses": [{"address": "Aristotle University of Thessaloniki", "lat": "40.62984145", "lng": "22.95889350", "type": "edu"}], "year": "2017", "pdf": "http://www.eurasip.org/Proceedings/Eusipco/Eusipco2017/papers/1570347567.pdf"}, {"id": "5fa04523ff13a82b8b6612250a39e1edb5066521", "title": "Dockerface: an easy to install and use Faster R-CNN face detector in a Docker container", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1708.04370.pdf"}, {"id": "f9fb7979af4233c2dd14813da94ec7c38ce9232a", "title": "Detecting Gaze Towards Eyes in Natural Social Interactions and Its Use in Child Assessment", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}, {"address": "University of Michigan", "lat": "42.29421420", "lng": "-83.71003894", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1902.00607.pdf"}, {"id": "68eb6e0e3660009e8a046bff15cef6fe87d46477", "title": "Multi-dropout regression for wide-angle landmark localization", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "9865fe20df8fe11717d92b5ea63469f59cf1635a", "title": "Wildest Faces: Face Detection and Recognition in Violent Settings", "addresses": [{"address": "Hacettepe University", "lat": "39.86742125", "lng": "32.73519072", "type": "edu"}, {"address": "Middle East Technical University", "lat": "39.87549675", "lng": "32.78553506", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1805.07566.pdf"}, {"id": "637b31157386efbde61505365c0720545248fbae", "title": "Deep learning with time-frequency representation for pulse estimation from facial videos", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "7c825562b3ff4683ed049a372cb6807abb09af2a", "title": "Finding Tiny Faces Supplementary Materials", "addresses": [{"address": "Robotics Institute", "lat": "13.65450525", "lng": "100.49423171", "type": "edu"}, {"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/7c82/5562b3ff4683ed049a372cb6807abb09af2a.pdf"}, {"id": "969fd48e1a668ab5d3c6a80a3d2aeab77067c6ce", "title": "End-To-End Face Detection and Recognition", "addresses": [{"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1703.10818.pdf"}, {"id": "d4f1eb008eb80595bcfdac368e23ae9754e1e745", "title": "Unconstrained Face Detection and Open-Set Face Recognition Challenge", "addresses": [{"address": "University of Colorado, Colorado Springs", "lat": "38.89207560", "lng": "-104.79716389", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1708.02337.pdf"}, {"id": "c7cd490e43ee4ff81e8f86f790063695369c2830", "title": "Use fast R-CNN and cascade structure for face detection", "addresses": [{"address": "Beijing FaceAll Co., Beijing, China", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}, {"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2016", "pdf": null}, {"id": "f27fd2a1bc229c773238f1912db94991b8bf389a", "title": "How do you develop a face detector for the unconstrained environment?", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2016", "pdf": null}, {"id": "3399f8f0dff8fcf001b711174d29c9d4fde89379", "title": "Face R-CNN", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1706.01061.pdf"}, {"id": "fb54d3c37dc82891ff9dc7dd8caf31de00c40d6a", "title": "Beauty and the Burst: Remote Identification of Encrypted Video Streams", "addresses": [{"address": "Tel Aviv University", "lat": "32.11198890", "lng": "34.80459702", "type": "edu"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/c21b/ccf1ab4bb090fd5fc1109421a1a3979e7106.pdf"}, {"id": "3fb4bf38d34f7f7e5b3df36de2413d34da3e174a", "title": "Persuasive Faces: Generating Faces in Advertisements", "addresses": [{"address": "University of Pittsburgh", "lat": "40.44415295", "lng": "-79.96243993", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1807.09882.pdf"}, {"id": "cde8186c38c04dacac2e1fac1c3c68cf46516b9f", "title": "Hierarchical Network for Facial Palsy Detection", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "", "pdf": "https://pdfs.semanticscholar.org/cde8/186c38c04dacac2e1fac1c3c68cf46516b9f.pdf"}, {"id": "f5eb411217f729ad7ae84bfd4aeb3dedb850206a", "title": "Tackling Low Resolution for Better Scene Understanding", "addresses": [{"address": "International Institute of Information Technology", "lat": "17.44549570", "lng": "78.34854698", "type": "edu"}], "year": "2018", "pdf": "https://pdfs.semanticscholar.org/f5eb/411217f729ad7ae84bfd4aeb3dedb850206a.pdf"}, {"id": "7071cd1ee46db4bc1824c4fd62d36f6d13cad08a", "title": "Face Detection through Scale-Friendly Deep Convolutional Networks", "addresses": [{"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1706.02863.pdf"}, {"id": "dcf71245addaf66a868221041aabe23c0a074312", "title": "S^3FD: Single Shot Scale-Invariant Face Detector", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1708.05237.pdf"}, {"id": "1e9f1bbb751fe538dde9f612f60eb946747defaa", "title": "Identity-aware convolutional neural networks for facial expression recognition", "addresses": [{"address": "Tampere University of Technology", "lat": "61.44964205", "lng": "23.85877462", "type": "edu"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/1e9f/1bbb751fe538dde9f612f60eb946747defaa.pdf"}, {"id": "d69271c7b77bc3a06882884c21aa1b609b3f76cc", "title": "FaceBoxes: A CPU real-time face detector with high accuracy", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1708.05234.pdf"}, {"id": "2e942d19333651bf6012374ea9e78d6937fd33ac", "title": "Detecting Faces Using Region-based Fully Convolutional Networks", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1709.05256.pdf"}, {"id": "657e702326a1cbc561e059476e9be4d417c37795", "title": "Face detection based on multi task learning and multi layer feature fusion", "addresses": [{"address": "SIASUN Robot and Automation, Shenyang, China", "lat": "41.80569900", "lng": "123.43147200", "type": "company"}, {"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "19458454308a9f56b7de76bf7d8ff8eaa52b0173", "title": "Deep Features for Recognizing Disguised Faces in the Wild", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "", "pdf": "https://pdfs.semanticscholar.org/1945/8454308a9f56b7de76bf7d8ff8eaa52b0173.pdf"}, {"id": "0aa0e5f96d512fcd2357129ad4363d6ae961327e", "title": "Unsupervised Hard Example Mining from Videos for Improved Object Detection", "addresses": [{"address": "University of Massachusetts", "lat": "42.38897850", "lng": "-72.52869870", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1808.04285.pdf"}, {"id": "d5d7e89e6210fcbaa52dc277c1e307632cd91dab", "title": "DOTA: A Large-scale Dataset for Object Detection in Aerial Images", "addresses": [{"address": "Wuhan University of Technology", "lat": "30.60903415", "lng": "114.35142840", "type": "edu"}, {"address": "Cornell University", "lat": "42.45055070", "lng": "-76.47835130", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1711.10398.pdf"}, {"id": "ed96f2eb1771f384df2349879970065a87975ca7", "title": "Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization", "addresses": [{"address": "University of Toronto", "lat": "43.66333345", "lng": "-79.39769975", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1805.12302.pdf"}, {"id": "b3b467961ba66264bb73ffe00b1830d7874ae8ce", "title": "Finding Tiny Faces", "addresses": [{"address": "Robotics Institute", "lat": "13.65450525", "lng": "100.49423171", "type": "edu"}, {"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1612.04402.pdf"}, {"id": "282503fa0285240ef42b5b4c74ae0590fe169211", "title": "Feeding Hand-Crafted Features for Enhancing the Performance of Convolutional Neural Networks", "addresses": [{"address": "Seoul National University", "lat": "37.26728000", "lng": "126.98411510", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1801.07848.pdf"}, {"id": "2f61d91033a06dd904ff9d1765d57e5b4d7f57a6", "title": "FCFD: Teach the machine to accomplish face detection step by step", "addresses": [{"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2016", "pdf": null}, {"id": "4e6c17966efae956133bf8f22edeffc24a0470c1", "title": "Face Classification: A Specialized Benchmark Study", "addresses": [{"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}, {"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "Macau University of Science and Technology", "lat": "22.15263985", "lng": "113.56803206", "type": "edu"}], "year": "2016", "pdf": "https://pdfs.semanticscholar.org/4e6c/17966efae956133bf8f22edeffc24a0470c1.pdf"}, {"id": "5d9f468a2841ea2f27bbe3ef2c6fe531d444be68", "title": "PT-NET: Improve object and face detection via a pre-trained CNN model", "addresses": [{"address": "Academy of Broadcasting Science, Beijing, China", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}, {"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "fdcca639b96aa982ae67544f58c7e60be9d0748e", "title": "DFN: Dual Fusion Networks for Single Stage Face Detection", "addresses": [{"address": "Northeastern University", "lat": "42.33836680", "lng": "-71.08793524", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "59e9934720baf3c5df3a0e1e988202856e1f83ce", "title": "UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking", "addresses": [{"address": "Hanyang University", "lat": "37.55572710", "lng": "127.04366420", "type": "edu"}], "year": "2015", "pdf": "https://arxiv.org/pdf/1511.04136.pdf"}, {"id": "25ff865460c2b5481fa4161749d5da8501010aa0", "title": "Seeing What is Not There: Learning Context to Determine Where Objects are Missing", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1702.07971.pdf"}, {"id": "7fcfd72ba6bc14bbb90b31fe14c2c77a8b220ab2", "title": "Robust FEC-CNN: A High Accuracy Facial Landmark Detection System", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": "http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/He_Robust_FEC-CNN_A_CVPR_2017_paper.pdf"}, {"id": "015df3b57e44b8ddc51c87e5255fa4940bd91963", "title": "DSFD: Dual Shot Face Detector", "addresses": [{"address": "Nanjing University", "lat": "32.05659570", "lng": "118.77408833", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1810.10220.pdf"}, {"id": "101d1cff1aa5590a1f79bc485cbfec094a995f74", "title": "Persuasive Faces: Generating Faces in Advertisements (Supplementary Material)", "addresses": [{"address": "University of Pittsburgh", "lat": "40.44415295", "lng": "-79.96243993", "type": "edu"}], "year": "2018", "pdf": "https://pdfs.semanticscholar.org/101d/1cff1aa5590a1f79bc485cbfec094a995f74.pdf"}, {"id": "d3b0839324d0091e70ce34f44c979b9366547327", "title": "Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection", "addresses": [{"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1804.10743.pdf"}, {"id": "a065080353d18809b2597246bb0b48316234c29a", "title": "FHEDN: A based on context modeling Feature Hierarchy Encoder-Decoder Network for face detection", "addresses": [{"address": "Chongqing University", "lat": "29.50841740", "lng": "106.57858552", "type": "edu"}], "year": "2017", "pdf": "https://arxiv.org/pdf/1712.03687.pdf"}, {"id": "849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b", "title": "ResNet Backbone Proposals Classification Loss Regression Loss Classification Loss Regression Loss RPN Classification Branch Box Regression Branch Conv Conv", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": "https://pdfs.semanticscholar.org/849f/891973ad2b6c6f70d7d43d9ac5805f1a1a5b.pdf"}, {"id": "ebb3d5c70bedf2287f9b26ac0031004f8f617b97", "title": "Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans", "addresses": [{"address": "Electrical and Computer Engineering", "lat": "33.58667840", "lng": "-101.87539204", "type": "edu"}, {"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2018", "pdf": null}, {"id": "aab3561acbd19f7397cbae39dd34b3be33220309", "title": "Quantization Mimic: Towards Very Tiny CNN for Object Detection", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}, {"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}, {"address": "SenseTime", "lat": "39.99300800", "lng": "116.32988200", "type": "company"}, {"address": "University of Sydney", "lat": "-33.88890695", "lng": "151.18943366", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1805.02152.pdf"}, {"id": "fc8990088e0f1f017540900bc3f5a4996192ff05", "title": "Hierarchical bilinear network for high performance face detection", "addresses": [{"address": "Chinese Academy of Science", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "8f71c97206a03c366ddefaa6812f865ac6df87e9", "title": "A face tracking framework based on convolutional neural networks and Kalman filter", "addresses": [{"address": "Huazhong University of Science and Technology", "lat": "30.50975370", "lng": "114.40628810", "type": "edu"}, {"address": "Xiamen University", "lat": "24.43994190", "lng": "118.09301781", "type": "edu"}], "year": "2017", "pdf": null}, {"id": "de79437f74e8e3b266afc664decf4e6e4bdf34d7", "title": "To face or not to face: Towards reducing false positive of face detection", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2016", "pdf": null}, {"id": "9ac43a98fe6fde668afb4fcc115e4ee353a6732d", "title": "Survey of Face Detection on Low-Quality Images", "addresses": [{"address": "University of Illinois, Urbana-Champaign", "lat": "40.11116745", "lng": "-88.22587665", "type": "edu"}], "year": "2018", "pdf": "https://arxiv.org/pdf/1804.07362.pdf"}, {"id": "c92bb26238f6e30196b0c4a737d8847e61cfb7d4", "title": "Beyond Context: Exploring Semantic Similarity for Tiny Face Detection", "addresses": [{"address": "Northwestern Polytechnical University", "lat": "34.24691520", "lng": "108.91061982", "type": "edu"}, {"address": "University of Technology Sydney", "lat": "-33.88096510", "lng": "151.20107299", "type": "edu"}, {"address": "Sun Yat-Sen University", "lat": "23.09461185", "lng": "113.28788994", "type": "edu"}], "year": "2018", "pdf": null}]} \ No newline at end of file
+{"id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "dataset": {"key": "wider_face", "name_short": "WIDER FACE", "using": "N", "ft_share": "1", "subset_of": "", "superset_of": "", "name_full": "Web Image Dataset for Event Recognition Face", "url": "http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/", "added_on": "", "faces": "", "pdf_paper": "Y", "comments": "data drom WIDER dataset", "": "", "relevance": ""}, "statistics": {"key": "wider_face", "name": "WIDER FACE", "berit": "Y", "charlie": "", "adam": "", "priority": "N", "wild": "Y", "indoor": "", "outdoor": "", "cyberspace": "Y", "names": "", "downloaded": "N", "year_start": "", "year_end": "", "year_published": "2016", "ongoing": "", "images": "32,203 ", "videos": "", "faces_unique": "0 ", "total_faces": "", "img_per_person": "", "num_cameras": "", "faces_persons": "393,703 ", "female": "", "male": "", "landmarks": "", "width": "", "height": "", "color": "", "gray": "", "derivative_of": "Y", "tags": "", "source": "wider", "purpose_short": "face detection benchmark dataset", "size_gb": "", "agreement": "NA", "agree_requied": "", "agreement_signed": "", "comment": "", "comment 2": "", "comment 3": "", "": ""}, "paper": {"paper_id": "52d7eb0fbc3522434c13cc247549f74bb9609c5d", "key": "wider_face", "title": "WIDER FACE: A Face Detection Benchmark", "year": "2016", "pdf": ["https://arxiv.org/pdf/1511.06523.pdf"], "address": "", "name": "WIDER FACE", "doi": []}, "address": null, "additional_papers": [], "citations": [{"id": "28646c6220848db46c6944967298d89a6559c700", "title": "It takes two to tango : Cascading off-the-shelf face detectors", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/2864/6c6220848db46c6944967298d89a6559c700.pdf"]}, {"id": "def2983576001bac7d6461d78451159800938112", "title": "The Do\u2019s and Don\u2019ts for CNN-Based Face Verification", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1705.07426.pdf"]}, {"id": "2d8001ffee6584b3f4d951d230dc00a06e8219f8", "title": "Feature Agglomeration Networks for Single Stage Face Detection", "addresses": [{"address": "Singapore Management University", "lat": "1.29500195", "lng": "103.84909214", "type": "edu"}, {"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.00721.pdf"]}, {"id": "d8fbd3a16d2e2e59ce0cff98b3fd586863878dc1", "title": "Face detection and recognition for home service robots with end-to-end deep neural networks", "addresses": [{"address": "Futurewei Technologies Inc., Santa Clara, CA", "lat": "37.37344400", "lng": "-121.96487270", "type": "company"}], "year": "2017", "pdf": ["http://mirlab.org/conference_papers/International_Conference/ICASSP%202017/pdfs/0002232.pdf"]}, {"id": "e8523c4ac9d7aa21f3eb4062e09f2a3bc1eedcf7", "title": "Toward End-to-End Face Recognition Through Alignment Learning", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1701.07174.pdf"]}, {"id": "4e30107ee6a2e087f14a7725e7fc5535ec2f5a5f", "title": "\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u043d\u043e\u0432\u043e\u0441\u0442\u043d\u044b\u0445 \u0441\u044e\u0436\u0435\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0441\u043e\u0431\u044b\u0442\u0438\u0439\u043d\u044b\u0445 \u0444\u043e\u0442\u043e\u0433\u0440\u0430\u0444\u0438\u0439 (News Stories Representation Using Event Photos)", "addresses": [{"address": "Lomonosov Moscow State University", "lat": "55.70229715", "lng": "37.53179777", "type": "edu"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/4e30/107ee6a2e087f14a7725e7fc5535ec2f5a5f.pdf"]}, {"id": "72cbbdee4f6eeee8b7dd22cea6092c532271009f", "title": "Masquer Hunter: Adversarial Occlusion-aware Face Detection", "addresses": [{"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1709.05188.pdf"]}, {"id": "bd236913cfe07896e171ece9bda62c18b8c8197e", "title": "Deep Learning with Energy-efficient Binary Gradient Cameras", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2016", "pdf": ["https://arxiv.org/pdf/1612.00986.pdf"]}, {"id": "e659221538d256b2c3e0724deff749eda903fc7d", "title": "Fine-Grained Head Pose Estimation Without Keypoints", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1710.00925.pdf"]}, {"id": "acee2201f8a15990551804dd382b86973eb7c0a8", "title": "To boost or not to boost? On the limits of boosted trees for object detection", "addresses": [{"address": "University of California, San Diego", "lat": "32.87935255", "lng": "-117.23110049", "type": "edu"}], "year": "2016", "pdf": ["https://arxiv.org/pdf/1701.01692.pdf"]}, {"id": "377f2b65e6a9300448bdccf678cde59449ecd337", "title": "Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results", "addresses": [{"address": "Johns Hopkins University", "lat": "39.32905300", "lng": "-76.61942500", "type": "edu"}, {"address": "Rutgers University", "lat": "40.47913175", "lng": "-74.43168868", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.10275.pdf"]}, {"id": "6dbdb07ce2991db0f64c785ad31196dfd4dae721", "title": "Seeing Small Faces from Robust Anchor's Perspective", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1802.09058.pdf"]}, {"id": "aa799d721f75510be236ac73f26ec92b0a89ab10", "title": "Computer Vision \u2013 ECCV 2018", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "f79e4ba09402adab54d2efadd1c4bfe4e20c5da5", "title": "A highly accurate facial region network for unconstrained face detection", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "3c97c32ff575989ef2869f86d89c63005fc11ba9", "title": "Face Detection with the Faster R-CNN", "addresses": [{"address": "University of Massachusetts", "lat": "42.38897850", "lng": "-72.52869870", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1606.03473.pdf"]}, {"id": "25c108a56e4cb757b62911639a40e9caf07f1b4f", "title": "Recurrent Scale Approximation for Object Detection in CNN", "addresses": [{"address": "SenseTime", "lat": "39.99300800", "lng": "116.32988200", "type": "company"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1707.09531.pdf"]}, {"id": "24d45df91ebcfac7a49cdfb7116e971e12880612", "title": "UNICITY: A depth maps database for people detection in security airlocks", "addresses": [{"address": "IDIAP Research Institute", "lat": "46.10923700", "lng": "7.08453549", "type": "edu"}], "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/24d4/5df91ebcfac7a49cdfb7116e971e12880612.pdf"]}, {"id": "7788fa76f1488b1597ee2bebc462f628e659f61e", "title": "A Privacy-Aware Architecture at the Edge for Autonomous Real-Time Identity Reidentification in Crowds", "addresses": [{"address": "University of Texas at San Antonio", "lat": "29.58333105", "lng": "-98.61944505", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "e4e07f5f201c6986e93ddb42dcf11a43c339ea2e", "title": "Cross-pose landmark localization using multi-dropout framework", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "11824658170994e4d4655e8f688bace16a0d3e48", "title": "Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Framework", "addresses": [{"address": "Qatar University", "lat": "25.37461295", "lng": "51.48980354", "type": "edu"}, {"address": "University of Warwick", "lat": "52.37931310", "lng": "-1.56042520", "type": "edu"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/1182/4658170994e4d4655e8f688bace16a0d3e48.pdf"]}, {"id": "beb49072f5ba79ed24750108c593e8982715498e", "title": "GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data", "addresses": [{"address": "Peking University", "lat": "39.99223790", "lng": "116.30393816", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1705.04932.pdf"]}, {"id": "15ee80e86e75bf1413dc38f521b9142b28fe02d1", "title": "Towards a deep learning framework for unconstrained face detection", "addresses": [{"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2016", "pdf": ["https://arxiv.org/pdf/1612.05322.pdf"]}, {"id": "cd023d2d067365c83d8e27431e83e7e66082f718", "title": "Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.06039.pdf"]}, {"id": "438e7999c937b94f0f6384dbeaa3febff6d283b6", "title": "Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild", "addresses": [{"address": "University of Surrey", "lat": "51.24303255", "lng": "-0.59001382", "type": "edu"}, {"address": "Jiangnan University", "lat": "31.48542550", "lng": "120.27395810", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1705.02402.pdf"]}, {"id": "35ccc836df60cd99c731412fe44156c7fd057b99", "title": "A cascade framework for masked face detection", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "Shanghai University", "lat": "31.32235655", "lng": "121.38400941", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "ac6c3b3e92ff5fbcd8f7967696c7aae134bea209", "title": "Deep Cascaded Bi-Network for Face Hallucination", "addresses": [{"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}, {"address": "Shenzhen Institutes of Advanced Technology", "lat": "22.59805605", "lng": "113.98533784", "type": "edu"}, {"address": "University of California, Merced", "lat": "37.36566745", "lng": "-120.42158888", "type": "edu"}], "year": "2016", "pdf": ["https://arxiv.org/pdf/1607.05046.pdf"]}, {"id": "4203f10b41e7931a63598989aa14478c04b725c9", "title": "Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1712.08263.pdf"]}, {"id": "cc70fb1ab585378c79a2ab94776723e597afe379", "title": "Detect face in the wild using CNN cascade with feature aggregation at multi-resolution", "addresses": [{"address": "Swansea University", "lat": "51.60915780", "lng": "-3.97934429", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "a896ddeb0d253739c9aaef7fc1f170a2ba8407d3", "title": "SSH: Single Stage Headless Face Detector", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.03979.pdf"]}, {"id": "eb87151fd2796ff5b4bbcf1906d41d53ac6c5595", "title": "Enhanced face detection using body part detections for wearable cameras", "addresses": [{"address": "IBM Thomas J. Watson Research Center", "lat": "41.21002475", "lng": "-73.80407056", "type": "company"}], "year": "2016", "pdf": []}, {"id": "185263189a30986e31566394680d6d16b0089772", "title": "Efficient Annotation of Objects for Video Analysis", "addresses": [{"address": "International Institute of Information Technology", "lat": "17.44549570", "lng": "78.34854698", "type": "edu"}], "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/1852/63189a30986e31566394680d6d16b0089772.pdf"]}, {"id": "19d4b3679294563247c126148912d44cbf03e40e", "title": "Value-Aware Resampling and Loss for Imbalanced Classification", "addresses": [{"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "853fc1794892175e2318f55785ca8e2ce6fd7537", "title": "FHEDN: A context modeling Feature Hierarchy Encoder-Decoder Network for face detection", "addresses": [{"address": "Chongqing University", "lat": "29.50841740", "lng": "106.57858552", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "ede5982980aa76deae8f9dc5143a724299d67742", "title": "Lightweight two-stream convolutional face detection", "addresses": [{"address": "Aristotle University of Thessaloniki", "lat": "40.62984145", "lng": "22.95889350", "type": "edu"}], "year": "2017", "pdf": ["http://www.eurasip.org/Proceedings/Eusipco/Eusipco2017/papers/1570347567.pdf"]}, {"id": "5fa04523ff13a82b8b6612250a39e1edb5066521", "title": "Dockerface: an easy to install and use Faster R-CNN face detector in a Docker container", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.04370.pdf"]}, {"id": "f9fb7979af4233c2dd14813da94ec7c38ce9232a", "title": "Detecting Gaze Towards Eyes in Natural Social Interactions and Its Use in Child Assessment", "addresses": [{"address": "Georgia Institute of Technology", "lat": "33.77603300", "lng": "-84.39884086", "type": "edu"}, {"address": "University of Michigan", "lat": "42.29421420", "lng": "-83.71003894", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1902.00607.pdf"]}, {"id": "68eb6e0e3660009e8a046bff15cef6fe87d46477", "title": "Multi-dropout regression for wide-angle landmark localization", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "9865fe20df8fe11717d92b5ea63469f59cf1635a", "title": "Wildest Faces: Face Detection and Recognition in Violent Settings", "addresses": [{"address": "Hacettepe University", "lat": "39.86742125", "lng": "32.73519072", "type": "edu"}, {"address": "Middle East Technical University", "lat": "39.87549675", "lng": "32.78553506", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.07566.pdf"]}, {"id": "637b31157386efbde61505365c0720545248fbae", "title": "Deep learning with time-frequency representation for pulse estimation from facial videos", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "7c825562b3ff4683ed049a372cb6807abb09af2a", "title": "Finding Tiny Faces Supplementary Materials", "addresses": [{"address": "Robotics Institute", "lat": "13.65450525", "lng": "100.49423171", "type": "edu"}, {"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/7c82/5562b3ff4683ed049a372cb6807abb09af2a.pdf"]}, {"id": "969fd48e1a668ab5d3c6a80a3d2aeab77067c6ce", "title": "End-To-End Face Detection and Recognition", "addresses": [{"address": "Zhejiang University", "lat": "30.19331415", "lng": "120.11930822", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1703.10818.pdf"]}, {"id": "d4f1eb008eb80595bcfdac368e23ae9754e1e745", "title": "Unconstrained Face Detection and Open-Set Face Recognition Challenge", "addresses": [{"address": "University of Colorado, Colorado Springs", "lat": "38.89207560", "lng": "-104.79716389", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.02337.pdf"]}, {"id": "c7cd490e43ee4ff81e8f86f790063695369c2830", "title": "Use fast R-CNN and cascade structure for face detection", "addresses": [{"address": "Beijing FaceAll Co., Beijing, China", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}, {"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2016", "pdf": []}, {"id": "f27fd2a1bc229c773238f1912db94991b8bf389a", "title": "How do you develop a face detector for the unconstrained environment?", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2016", "pdf": []}, {"id": "3399f8f0dff8fcf001b711174d29c9d4fde89379", "title": "Face R-CNN", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1706.01061.pdf"]}, {"id": "fb54d3c37dc82891ff9dc7dd8caf31de00c40d6a", "title": "Beauty and the Burst: Remote Identification of Encrypted Video Streams", "addresses": [{"address": "Tel Aviv University", "lat": "32.11198890", "lng": "34.80459702", "type": "edu"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/c21b/ccf1ab4bb090fd5fc1109421a1a3979e7106.pdf"]}, {"id": "3fb4bf38d34f7f7e5b3df36de2413d34da3e174a", "title": "Persuasive Faces: Generating Faces in Advertisements", "addresses": [{"address": "University of Pittsburgh", "lat": "40.44415295", "lng": "-79.96243993", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1807.09882.pdf"]}, {"id": "cde8186c38c04dacac2e1fac1c3c68cf46516b9f", "title": "Hierarchical Network for Facial Palsy Detection", "addresses": [{"address": "National Taiwan University of Science and Technology", "lat": "25.01353105", "lng": "121.54173736", "type": "edu"}], "year": "", "pdf": ["https://pdfs.semanticscholar.org/cde8/186c38c04dacac2e1fac1c3c68cf46516b9f.pdf"]}, {"id": "f5eb411217f729ad7ae84bfd4aeb3dedb850206a", "title": "Tackling Low Resolution for Better Scene Understanding", "addresses": [{"address": "International Institute of Information Technology", "lat": "17.44549570", "lng": "78.34854698", "type": "edu"}], "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/f5eb/411217f729ad7ae84bfd4aeb3dedb850206a.pdf"]}, {"id": "7071cd1ee46db4bc1824c4fd62d36f6d13cad08a", "title": "Face Detection through Scale-Friendly Deep Convolutional Networks", "addresses": [{"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1706.02863.pdf"]}, {"id": "dcf71245addaf66a868221041aabe23c0a074312", "title": "S^3FD: Single Shot Scale-Invariant Face Detector", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.05237.pdf"]}, {"id": "1e9f1bbb751fe538dde9f612f60eb946747defaa", "title": "Identity-aware convolutional neural networks for facial expression recognition", "addresses": [{"address": "Tampere University of Technology", "lat": "61.44964205", "lng": "23.85877462", "type": "edu"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/1e9f/1bbb751fe538dde9f612f60eb946747defaa.pdf"]}, {"id": "d69271c7b77bc3a06882884c21aa1b609b3f76cc", "title": "FaceBoxes: A CPU real-time face detector with high accuracy", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1708.05234.pdf"]}, {"id": "2e942d19333651bf6012374ea9e78d6937fd33ac", "title": "Detecting Faces Using Region-based Fully Convolutional Networks", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1709.05256.pdf"]}, {"id": "657e702326a1cbc561e059476e9be4d417c37795", "title": "Face detection based on multi task learning and multi layer feature fusion", "addresses": [{"address": "SIASUN Robot and Automation, Shenyang, China", "lat": "41.80569900", "lng": "123.43147200", "type": "company"}, {"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "19458454308a9f56b7de76bf7d8ff8eaa52b0173", "title": "Deep Features for Recognizing Disguised Faces in the Wild", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "", "pdf": ["https://pdfs.semanticscholar.org/1945/8454308a9f56b7de76bf7d8ff8eaa52b0173.pdf"]}, {"id": "0aa0e5f96d512fcd2357129ad4363d6ae961327e", "title": "Unsupervised Hard Example Mining from Videos for Improved Object Detection", "addresses": [{"address": "University of Massachusetts", "lat": "42.38897850", "lng": "-72.52869870", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1808.04285.pdf"]}, {"id": "d5d7e89e6210fcbaa52dc277c1e307632cd91dab", "title": "DOTA: A Large-scale Dataset for Object Detection in Aerial Images", "addresses": [{"address": "Wuhan University of Technology", "lat": "30.60903415", "lng": "114.35142840", "type": "edu"}, {"address": "Cornell University", "lat": "42.45055070", "lng": "-76.47835130", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1711.10398.pdf"]}, {"id": "ed96f2eb1771f384df2349879970065a87975ca7", "title": "Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization", "addresses": [{"address": "University of Toronto", "lat": "43.66333345", "lng": "-79.39769975", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.12302.pdf"]}, {"id": "b3b467961ba66264bb73ffe00b1830d7874ae8ce", "title": "Finding Tiny Faces", "addresses": [{"address": "Robotics Institute", "lat": "13.65450525", "lng": "100.49423171", "type": "edu"}, {"address": "Carnegie Mellon University", "lat": "37.41021930", "lng": "-122.05965487", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1612.04402.pdf"]}, {"id": "282503fa0285240ef42b5b4c74ae0590fe169211", "title": "Feeding Hand-Crafted Features for Enhancing the Performance of Convolutional Neural Networks", "addresses": [{"address": "Seoul National University", "lat": "37.26728000", "lng": "126.98411510", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1801.07848.pdf"]}, {"id": "2f61d91033a06dd904ff9d1765d57e5b4d7f57a6", "title": "FCFD: Teach the machine to accomplish face detection step by step", "addresses": [{"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2016", "pdf": []}, {"id": "4e6c17966efae956133bf8f22edeffc24a0470c1", "title": "Face Classification: A Specialized Benchmark Study", "addresses": [{"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}, {"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "Macau University of Science and Technology", "lat": "22.15263985", "lng": "113.56803206", "type": "edu"}], "year": "2016", "pdf": ["https://pdfs.semanticscholar.org/4e6c/17966efae956133bf8f22edeffc24a0470c1.pdf"]}, {"id": "5d9f468a2841ea2f27bbe3ef2c6fe531d444be68", "title": "PT-NET: Improve object and face detection via a pre-trained CNN model", "addresses": [{"address": "Academy of Broadcasting Science, Beijing, China", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}, {"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "fdcca639b96aa982ae67544f58c7e60be9d0748e", "title": "DFN: Dual Fusion Networks for Single Stage Face Detection", "addresses": [{"address": "Northeastern University", "lat": "42.33836680", "lng": "-71.08793524", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "59e9934720baf3c5df3a0e1e988202856e1f83ce", "title": "UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking", "addresses": [{"address": "Hanyang University", "lat": "37.55572710", "lng": "127.04366420", "type": "edu"}], "year": "2015", "pdf": ["https://arxiv.org/pdf/1511.04136.pdf"]}, {"id": "25ff865460c2b5481fa4161749d5da8501010aa0", "title": "Seeing What is Not There: Learning Context to Determine Where Objects are Missing", "addresses": [{"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1702.07971.pdf"]}, {"id": "7fcfd72ba6bc14bbb90b31fe14c2c77a8b220ab2", "title": "Robust FEC-CNN: A High Accuracy Facial Landmark Detection System", "addresses": [{"address": "Chinese Academy of Sciences", "lat": "40.00447950", "lng": "116.37023800", "type": "edu"}, {"address": "University of Chinese Academy of Sciences", "lat": "39.90828040", "lng": "116.24585270", "type": "edu"}], "year": "2017", "pdf": ["http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/He_Robust_FEC-CNN_A_CVPR_2017_paper.pdf"]}, {"id": "015df3b57e44b8ddc51c87e5255fa4940bd91963", "title": "DSFD: Dual Shot Face Detector", "addresses": [{"address": "Nanjing University", "lat": "32.05659570", "lng": "118.77408833", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1810.10220.pdf"]}, {"id": "101d1cff1aa5590a1f79bc485cbfec094a995f74", "title": "Persuasive Faces: Generating Faces in Advertisements (Supplementary Material)", "addresses": [{"address": "University of Pittsburgh", "lat": "40.44415295", "lng": "-79.96243993", "type": "edu"}], "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/101d/1cff1aa5590a1f79bc485cbfec094a995f74.pdf"]}, {"id": "d3b0839324d0091e70ce34f44c979b9366547327", "title": "Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection", "addresses": [{"address": "Beijing University of Posts and Telecommunications", "lat": "39.96014880", "lng": "116.35193921", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.10743.pdf"]}, {"id": "a065080353d18809b2597246bb0b48316234c29a", "title": "FHEDN: A based on context modeling Feature Hierarchy Encoder-Decoder Network for face detection", "addresses": [{"address": "Chongqing University", "lat": "29.50841740", "lng": "106.57858552", "type": "edu"}], "year": "2017", "pdf": ["https://arxiv.org/pdf/1712.03687.pdf"]}, {"id": "849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b", "title": "ResNet Backbone Proposals Classification Loss Regression Loss Classification Loss Regression Loss RPN Classification Branch Box Regression Branch Conv Conv", "addresses": [{"address": "Tencent", "lat": "22.54471540", "lng": "113.93571640", "type": "company"}], "year": "2017", "pdf": ["https://pdfs.semanticscholar.org/849f/891973ad2b6c6f70d7d43d9ac5805f1a1a5b.pdf"]}, {"id": "ebb3d5c70bedf2287f9b26ac0031004f8f617b97", "title": "Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans", "addresses": [{"address": "Electrical and Computer Engineering", "lat": "33.58667840", "lng": "-101.87539204", "type": "edu"}, {"address": "University of Maryland", "lat": "39.28996850", "lng": "-76.62196103", "type": "edu"}], "year": "2018", "pdf": []}, {"id": "aab3561acbd19f7397cbae39dd34b3be33220309", "title": "Quantization Mimic: Towards Very Tiny CNN for Object Detection", "addresses": [{"address": "Tsinghua University", "lat": "40.00229045", "lng": "116.32098908", "type": "edu"}, {"address": "Chinese University of Hong Kong", "lat": "22.42031295", "lng": "114.20788644", "type": "edu"}, {"address": "SenseTime", "lat": "39.99300800", "lng": "116.32988200", "type": "company"}, {"address": "University of Sydney", "lat": "-33.88890695", "lng": "151.18943366", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1805.02152.pdf"]}, {"id": "fc8990088e0f1f017540900bc3f5a4996192ff05", "title": "Hierarchical bilinear network for high performance face detection", "addresses": [{"address": "Chinese Academy of Science", "lat": "39.90419990", "lng": "116.40739630", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "8f71c97206a03c366ddefaa6812f865ac6df87e9", "title": "A face tracking framework based on convolutional neural networks and Kalman filter", "addresses": [{"address": "Huazhong University of Science and Technology", "lat": "30.50975370", "lng": "114.40628810", "type": "edu"}, {"address": "Xiamen University", "lat": "24.43994190", "lng": "118.09301781", "type": "edu"}], "year": "2017", "pdf": []}, {"id": "de79437f74e8e3b266afc664decf4e6e4bdf34d7", "title": "To face or not to face: Towards reducing false positive of face detection", "addresses": [{"address": "University of Queensland", "lat": "-27.49741805", "lng": "153.01316956", "type": "edu"}], "year": "2016", "pdf": []}, {"id": "9ac43a98fe6fde668afb4fcc115e4ee353a6732d", "title": "Survey of Face Detection on Low-Quality Images", "addresses": [{"address": "University of Illinois, Urbana-Champaign", "lat": "40.11116745", "lng": "-88.22587665", "type": "edu"}], "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.07362.pdf"]}, {"id": "c92bb26238f6e30196b0c4a737d8847e61cfb7d4", "title": "Beyond Context: Exploring Semantic Similarity for Tiny Face Detection", "addresses": [{"address": "Northwestern Polytechnical University", "lat": "34.24691520", "lng": "108.91061982", "type": "edu"}, {"address": "University of Technology Sydney", "lat": "-33.88096510", "lng": "151.20107299", "type": "edu"}, {"address": "Sun Yat-Sen University", "lat": "23.09461185", "lng": "113.28788994", "type": "edu"}], "year": "2018", "pdf": []}]} \ No newline at end of file