Kaiming He - FAIR

• https://scholar.google.com/citations?view_op=top_venues&hl=en
• https://arxiv.org/abs/1609.08144
• https://arxiv.org/abs/1609.03499
• https://www.nature.com/articles/nature24270
• https://gkioxari.github.io/Tutorials/eccv2018/index.html
• https://sites.google.com/view/cvpr2018-recognition-tutorial
• https://instancetutorial.github.io/
• http://deeplearning.csail.mit.edu/
• http://icml.cc/2016/?page_id=97
• http://mp7.watson.ibm.com/ICCV2015/ObjectDetectionICCV2015.html
• http://scholar.google.com/citations?user=DhtAFkwAAAAJ&hl=en
• https://arxiv.org/abs/1904.01569
• https://arxiv.org/abs/1903.12174
• https://arxiv.org/abs/1904.09664
• https://arxiv.org/abs/1811.08883
• https://arxiv.org/abs/1812.03982
• https://arxiv.org/abs/1812.03411
• https://github.com/facebookresearch/ImageNet-Adversarial-Training
• https://arxiv.org/abs/1812.05038
• https://arxiv.org/abs/1901.02446
• http://presentations.cocodataset.org/COCO17-Stuff-FAIR.pdf
• https://arxiv.org/abs/1801.00868
• https://arxiv.org/abs/1806.05662
• https://eccv2018.org/news/eccv-awards/
• https://arxiv.org/abs/1803.08494
• https://github.com/facebookresearch/Detectron/blob/master/projects/GN
• https://arxiv.org/abs/1805.00932
• https://arxiv.org/abs/1711.07971
• https://github.com/facebookresearch/video-nonlocal-net
• https://arxiv.org/abs/1712.04440
• https://arxiv.org/abs/1704.07333
• https://arxiv.org/abs/1711.10370
• https://www.computer.org/web/tcpami/iccv-best-paper-award
• https://arxiv.org/abs/1703.06870
• https://www.youtube.com/watch?v=g7z4mkfRjI4
• http://presentations.cocodataset.org/COCO17-Detect-MaskRCNN.pptx
• https://github.com/facebookresearch/Detectron
• https://arxiv.org/abs/1708.02002
• https://arxiv.org/abs/1708.02901
• https://arxiv.org/abs/1706.02677
• https://arxiv.org/abs/1612.03144
• https://arxiv.org/abs/1611.05431
• https://github.com/facebookresearch/ResNeXt
• http://arxiv.org/abs/1605.06409
• https://github.com/daijifeng001/r-fcn
• http://arxiv.org/abs/1607.07032
• https://github.com/zhangliliang/RPN_BF/tree/RPN-pedestrian
• http://arxiv.org/abs/1603.08678
• http://arxiv.org/abs/1603.05027
• https://github.com/KaimingHe/resnet-1k-layers
• http://www.computer.org/portal/web/tcpami/CVPR-Best-Papers
• http://arxiv.org/abs/1512.03385
• https://github.com/KaimingHe/deep-residual-networks
• https://www.youtube.com/watch?v=1PGLj-uKT1w&feature=youtu.be
• http://image-net.org/challenges/LSVRC/2015/
• http://mscoco.org/dataset/#detections-challenge2015
• http://arxiv.org/abs/1512.04412
• https://github.com/daijifeng001/mnc
• http://arxiv.org/abs/1604.05144
• http://research.microsoft.com/en-us/um/people/jifdai/downloads/scribble_sup/
• http://arxiv.org/abs/1506.01497
• http://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf
• https://github.com/shaoqingren/faster_rcnn
• https://github.com/rbgirshick/py-faster-rcnn
• http://arxiv.org/abs/1504.06066
• http://arxiv.org/abs/1503.01640
• http://arxiv.org/abs/1502.01852
• http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/He_Delving_Deep_into_ICCV_2015_paper.pdf
• http://arxiv.org/abs/1412.1710
• http://arxiv.org/abs/1412.1283
• https://github.com/daijifeng001/MNC#2-training-of-cfm-for-instance-aware-semantic-segmentation
• http://arxiv.org/abs/1505.06798
• http://arxiv.org/abs/1411.4229
• http://arxiv.org/abs/1406.4729
• https://github.com/ShaoqingRen/SPP_net
• http://image-net.org/challenges/LSVRC/2014/results
• http://arxiv.org/abs/1501.00092
• http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html
• https://github.com/nagadomi/waifu2x#waifu2x
• https://www.computer.org/web/tcpami/young-researcher-award
• http://www.easycounter.com/