![]() Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross GirshickĬomputer Vision and Pattern Recognition ( CVPR), 2020 ( Oral). Momentum Contrast for Unsupervised Visual Representation Learning Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He Improved Baselines with Momentum Contrastive Learning International Conference on Machine Learning ( ICML), 2020Īre Labels Necessary for Neural Architecture Search?Ĭhenxi Liu, Piotr Dollár, Kaiming He, Ross Girshick, Alan Yuille, and Saining XieĮuropean Conference on Computer Vision ( ECCV), 2020 ( Spotlight) Jiaxuan You, Jure Leskovec, Kaiming He, and Saining Xie International Conference on Computer Vision ( ICCV), 2021 ( Oral)Ī Large-Scale Study on Unsupervised Spatiotemporal Representation LearningĬhristoph Feichtenhofer, Haoqi Fan, Bo Xiong, Ross Girshick, and Kaiming HeĬomputer Vision and Pattern Recognition ( CVPR), 2021Įxploring Simple Siamese Representation LearningĬomputer Vision and Pattern Recognition ( CVPR), 2021 ( Oral). Xinlei Chen *, Saining Xie *, and Kaiming He Best Paper NomineeĪn Empirical Study of Training Self-Supervised Vision Transformers Kaiming He *, Xinlei Chen *, Saining Xie, Yanghao Li, Piotr Dollár, and Ross GirshickĬomputer Vision and Pattern Recognition ( CVPR), 2022 ( Oral). Masked Autoencoders Are Scalable Vision Learners Yanghao Li, Saining Xie, Xinlei Chen, Piotr Dollár, Kaiming He, and Ross Girshick Yanghao Li, Hanzi Mao, Ross Girshick *, and Kaiming He *Įuropean Conference on Computer Vision ( ECCV), 2022īenchmarking Detection Transfer Learning with Vision Transformers Masked Autoencoders As Spatiotemporal LearnersĬhristoph Feichtenhofer *, Haoqi Fan *, Yanghao Li, and Kaiming HeĬonference on Neural Information Processing Systems ( NeurIPS), 2022Įxploring Plain Vision Transformer Backbones for Object Detection Yanghao Li *, Haoqi Fan *, Ronghang Hu *, Christoph Feichtenhofer †, and Kaiming He †Ĭomputer Vision and Pattern Recognition ( CVPR), 2023 Scaling Language-Image Pre-training via Masking He received his PhD degree from the Chinese University of Hong Kong in 2011, and his B.S. He is a recipient of several prestigious awards in computer vision, including the PAMI Young Researcher Award in 2018, the Best Paper Award in CVPR 2009, CVPR 2016, ICCV 2017, the Best Student Paper Award in ICCV 2017, the Best Paper Honorable Mention in ECCV 2018, CVPR 2021, and the Everingham Prize in ICCV 2021.īefore joining FAIR in 2016, he was with Microsoft Research Asia (MSRA) from 2011 to 2016. ![]() His publications have over 400,000 citations (as of March 2022) with an increase of over 100,000 per year. In recent years, his explorative works on self-supervised learning are the top cited papers published in CVPR 2020, 2021, 2022. His works on object detection and segmentation, including Faster R-CNN and Mask R-CNN, have made significant impact and are among the most cited papers in these areas. The residual connection is a fundamental component in modern deep learning models (e.g., Transformers, AlphaGo Zero). His paper on Deep Residual Networks (ResNets) is the most cited paper in all research areas in Google Scholar Metrics 2019, 2020, 2021. He has published a series of highly influential papers in computer vision and deep learning. His research areas include computer vision and deep learning. Kaiming He is a Research Scientist at Facebook AI Research (FAIR). Facebook AI Research (FAIR), Menlo Park, CA
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