Associate Professor, EECS, MIT

Office: 45-701H, 51 Vassar St, Cambridge, MA 02139

kaiming@mit.edu

I am an Associate Professor of the Department of Electrical Engineering and Computer Science (EECS) at Massachusetts Institute of Technology (MIT), as of Feb. 2024. My research covers a wide range of topics in computer vision and deep learning. Through the lens of computer vision problems, I aim to develop generalizable methods applicable to various domains. My research currently focuses on building computer models that can learn representations and develop intelligence from and for the complex world. The long-term goal of my research is to augment human intelligence with more capable artificial intelligence.

I am best known for my work on Deep Residual Networks (ResNets), with the residual connections therein now being used everywhere in modern deep learning models, including Transformers (e.g., GPT, ChatGPT), AlphaGo Zero, AlphaFold, Diffusion Models, and more. I am also known for my work on visual object detection and segmentation (e.g., Faster R-CNN, Mask R-CNN) and visual self-supervised learning (e.g., MoCo, MAE). I am a recipient of several prestigious awards, 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. My publications have over 500,000 citations (as of Nov. 2023) with an increase of over 100,000 per year.

Before joining MIT, I was a Research Scientist at Facebook AI Research (FAIR) from 2016 to 2024, and a Researcher at Microsoft Research Asia (MSRA) from 2011 to 2016. I received my PhD degree from the Chinese University of Hong Kong in 2011, and my B.S. degree from Tsinghua University in 2007.

Prospective PhD students: if you are interested in joining my group as a PhD, please submit your application to the EECS admission process (opening Sept.) and tag my name in the system.

Prospective interns and post-docs: if you are interested in joining my group, please email me with your CV and a short research statement.

Autoregressive Image Generation without Vector Quantization
Tianhong Li, Yonglong Tian, He Li, Mingyang Deng, and Kaiming He
Conference on Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)
arXiv   code

Return of Unconditional Generation: A Self-supervised Representation Generation Method
Tianhong Li, Dina Katabi, and Kaiming He
Conference on Neural Information Processing Systems (NeurIPS), 2024 (Oral)
arXiv   code

Physically Compatible 3D Object Modeling from a Single Image
Minghao Guo, Bohan Wang, Pingchuan Ma, Tianyuan Zhang, Crystal Elaine Owens, Chuang Gan, Joshua B. Tenenbaum, Kaiming He, and Wojciech Matusik
Conference on Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)
arXiv   project

Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers
Lirui Wang, Xinlei Chen, Jialiang Zhao, and Kaiming He
Conference on Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)
arXiv

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes
Minghao Guo, Bohan Wang, Kaiming He, and Wojciech Matusik
Tech report, May 2024
arXiv   code

Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning
Linsen Li, Pratyush Anand, Kaiming He, and Dirk Englund
Tech report, May 2024
arXiv

A Decade's Battle on Dataset Bias: Are We There Yet?
Zhuang Liu and Kaiming He
Tech report, Mar. 2024
arXiv

Deconstructing Denoising Diffusion Models for Self-Supervised Learning
Xinlei Chen, Zhuang Liu, Saining Xie, and Kaiming He
Tech report, Jan. 2024
arXiv

Scaling Language-Image Pre-training via Masking
Yanghao Li*, Haoqi Fan*, Ronghang Hu*, Christoph Feichtenhofer^†, and Kaiming He^†
Computer Vision and Pattern Recognition (CVPR), 2023
arXiv   code

Masked Autoencoders As Spatiotemporal Learners
Christoph Feichtenhofer*, Haoqi Fan*, Yanghao Li, and Kaiming He
Conference on Neural Information Processing Systems (NeurIPS), 2022
arXiv   code

Exploring Plain Vision Transformer Backbones for Object Detection
Yanghao Li, Hanzi Mao, Ross Girshick*, and Kaiming He*
European Conference on Computer Vision (ECCV), 2022
arXiv   code

Benchmarking Detection Transfer Learning with Vision Transformers
Yanghao Li, Saining Xie, Xinlei Chen, Piotr Dollár, Kaiming He, and Ross Girshick
Tech report, Nov. 2021
arXiv

Masked Autoencoders Are Scalable Vision Learners
Kaiming He*, Xinlei Chen*, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick
Computer Vision and Pattern Recognition (CVPR), 2022 (Oral). Best Paper Nominee
arXiv   code

An Empirical Study of Training Self-Supervised Vision Transformers
Xinlei Chen*, Saining Xie*, and Kaiming He
International Conference on Computer Vision (ICCV), 2021 (Oral)
arXiv   code

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
Christoph Feichtenhofer, Haoqi Fan, Bo Xiong, Ross Girshick, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2021
arXiv

Exploring Simple Siamese Representation Learning
Xinlei Chen and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2021 (Oral). Best Paper Honorable Mention
arXiv   code

Graph Structure of Neural Networks
Jiaxuan You, Jure Leskovec, Kaiming He, and Saining Xie
International Conference on Machine Learning (ICML), 2020
arXiv

Are Labels Necessary for Neural Architecture Search?
Chenxi Liu, Piotr Dollár, Kaiming He, Ross Girshick, Alan Yuille, and Saining Xie
European Conference on Computer Vision (ECCV), 2020 (Spotlight)
arXiv

Improved Baselines with Momentum Contrastive Learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He
Tech report, Mar. 2020
arXiv   code

Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick
Computer Vision and Pattern Recognition (CVPR), 2020 (Oral). Best Paper Nominee
arXiv   code

PointRend: Image Segmentation as Rendering
Alexander Kirillov, Yuxin Wu, Kaiming He, and Ross Girshick
Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)
arXiv   code

A Multigrid Method for Efficiently Training Video Models
Chao-Yuan Wu, Ross Girshick, Kaiming He, Christoph Feichtenhofer, and Philipp Krähenbühl
Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)
arXiv   code

Designing Network Design Spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár
Computer Vision and Pattern Recognition (CVPR), 2020
arXiv   code

Exploring Randomly Wired Neural Networks for Image Recognition
Saining Xie, Alexander Kirillov, Ross Girshick, and Kaiming He
International Conference on Computer Vision (ICCV), 2019 (Oral)
arXiv

SlowFast Networks for Video Recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He
International Conference on Computer Vision (ICCV), 2019 (Oral)
arXiv   code

Deep Hough Voting for 3D Object Detection in Point Clouds
Charles R. Qi, Or Litany, Kaiming He, and Leonidas J. Guibas
International Conference on Computer Vision (ICCV), 2019 (Oral). Best Paper Nominee
arXiv   code

TensorMask: A Foundation for Dense Object Segmentation
Xinlei Chen, Ross Girshick, Kaiming He, and Piotr Dollár
International Conference on Computer Vision (ICCV), 2019
arXiv   code

Rethinking ImageNet Pre-training
Kaiming He, Ross Girshick, and Piotr Dollár
International Conference on Computer Vision (ICCV), 2019
arXiv

Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2019
arXiv   code

Long-Term Feature Banks for Detailed Video Understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, and Ross Girshick
Computer Vision and Pattern Recognition (CVPR), 2019 (Oral)
arXiv   code

Panoptic Feature Pyramid Networks
Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár
Computer Vision and Pattern Recognition (CVPR), 2019 (Oral)
arXiv    code    slides: COCO 2017 workshop

Panoptic Segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár
Computer Vision and Pattern Recognition (CVPR), 2019
arXiv

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations
Zhilin Yang*, Jake Zhao*, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, and Yann LeCun
Conference on Neural Information Processing Systems (NeurIPS), 2018
arXiv

Group Normalization
Yuxin Wu and Kaiming He
European Conference on Computer Vision (ECCV), 2018 (Oral). Best Paper Honorable Mention
International Journal of Computer Vision (IJCV), accepted in 2019
arXiv   code   slides

Exploring the Limits of Weakly Supervised Pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten
European Conference on Computer Vision (ECCV), 2018
arXiv   code

Non-local Neural Networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2018
arXiv   code

Data Distillation: Towards Omni-Supervised Learning
Ilija Radosavovic, Piotr Dollár, Ross Girshick, Georgia Gkioxari, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2018
arXiv

Detecting and Recognizing Human-Object Interactions
Georgia Gkioxari, Ross Girshick, Piotr Dollár, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2018 (Spotlight)
arXiv

Learning to Segment Every Thing
Ronghang Hu, Piotr Dollár, Kaiming He, Trevor Darrell, and Ross Girshick
Computer Vision and Pattern Recognition (CVPR), 2018
arXiv

Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick
International Conference on Computer Vision (ICCV), 2017 (Oral). ICCV Best Paper Award (Marr Prize)
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2018
arXiv   talk   slides: ICCV tutorial  ICCV oral  COCO workshop   code

Focal Loss for Dense Object Detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár
International Conference on Computer Vision (ICCV), 2017 (Oral). ICCV Best Student Paper Award
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2018
arXiv   code

Transitive Invariance for Self-supervised Visual Representation Learning
Xiaolong Wang, Kaiming He, and Abhinav Gupta
International Conference on Computer Vision (ICCV), 2017
arXiv

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He
Tech report, June 2017
arXiv

Feature Pyramid Networks for Object Detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie
Computer Vision and Pattern Recognition (CVPR), 2017
arXiv   code

Aggregated Residual Transformations for Deep Neural Networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He
Computer Vision and Pattern Recognition (CVPR), 2017
arXiv   code

R-FCN: Object Detection via Region-based Fully Convolutional Networks
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun
Conference on Neural Information Processing Systems (NeurIPS), 2016
arXiv   code

Is Faster R-CNN Doing Well for Pedestrian Detection?
Liliang Zhang, Liang Lin, Xiaodan Liang, and Kaiming He
European Conference on Computer Vision (ECCV), 2016
arXiv   code

Instance-sensitive Fully Convolutional Networks
Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, and Jian Sun
European Conference on Computer Vision (ECCV), 2016
arXiv

Identity Mappings in Deep Residual Networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
European Conference on Computer Vision (ECCV), 2016 (Spotlight)
arXiv   code

Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2016 (Oral). CVPR Best Paper Award
arXiv   code   talk   slides: ILSVRC workshop  ICML tutorial  CVPR oral
ILSVRC & COCO competitions 2015: we won the 1st places in ImageNet classification, ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation!

Instance-aware Semantic Segmentation via Multi-task Network Cascades
Jifeng Dai, Kaiming He, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2016 (Oral)
arXiv   code
1st place of COCO 2015 segmentation competition

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2016 (Oral)
arXiv   project

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun
Conference on Neural Information Processing Systems (NeurIPS), 2015
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2016
arXiv   NeurIPS version   code-matlab   code-python

Object Detection Networks on Convolutional Feature Maps
Shaoqing Ren, Kaiming He, Ross Girshick, Xiangyu Zhang, and Jian Sun
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2016
arXiv

BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
Jifeng Dai, Kaiming He, and Jian Sun
International Conference on Computer Vision (ICCV), 2015
arXiv

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
International Conference on Computer Vision (ICCV), 2015
arXiv   ICCV version
The first to surpass human-level performance

Convolutional Neural Networks at Constrained Time Cost
Kaiming He and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2015
arXiv

Convolutional Feature Masking for Joint Object and Stuff Segmentation
Jifeng Dai, Kaiming He, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2015
arXiv   code

Efficient and Accurate Approximations of Nonlinear Convolutional Networks
Xiangyu Zhang, Jianhua Zou, Xiang Ming, Kaiming He, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2015
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2015
PAMI version   CVPR version

Sparse Projections for High-Dimensional Binary Codes
Yan Xia, Kaiming He, Pushmeet Kohli, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2015
paper   code

A Geodesic-Preserving Method for Image Warping
Dongping Li, Kaiming He, Jian Sun, and Kun Zhou
Computer Vision and Pattern Recognition (CVPR), 2015
paper

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
European Conference on Computer Vision (ECCV), 2014
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2015
arXiv   project   slides   poster   code
ILSVRC 2014 - We ranked 2nd in detection and 3rd in classification.
100x faster than R-CNN for object detection

Learning a Deep Convolutional Network for Image Super-Resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang
European Conference on Computer Vision (ECCV), 2014
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2015
arXiv   ECCV version   code
waifu2x

Graph Cuts for Supervised Binary Coding
Tiezheng Ge, Kaiming He, and Jian Sun
European Conference on Computer Vision (ECCV), 2014
paper

Product Sparse Coding
Tiezheng Ge, Kaiming He, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2014
paper

Content-Aware Rotation
Kaiming He, Huiwen Chang, and Jian Sun
International Conference on Computer Vision (ICCV), 2013
paper   image   project

Joint Inverted Indexing
Yan Xia, Kaiming He, Fang Wen, and Jian Sun
International Conference on Computer Vision (ICCV), 2013
paper   project

Constant Time Weighted Median Filtering for Stereo Matching and Beyond
Ziyang Ma, Kaiming He, Yichen Wei, Jian Sun, and Enhua Wu
International Conference on Computer Vision (ICCV), 2013
paper   supp   code

Rectangling Panoramic Images via Warping
Kaiming He, Huiwen Chang, and Jian Sun
ACM Transactions on Graphics, Proceedings of ACM SIGGRAPH, 2013
paper   image   slides   project

Optimized Product Quantization for Approximate Nearest Neighbor Search
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2013
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2013
paper   PAMI version   supp   code   project

K-means Hashing: an Affinity-Preserving Quantization Method for Learning Binary Compact Codes
Kaiming He, Fang Wen, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2013
paper 

Statistics of Patch Offsets for Image Completion
Kaiming He and Jian Sun
European Conference on Computer Vision (ECCV), 2012
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2014
paper   PAMI version   supp   project

Computing Nearest-Neighbor Fields via Propagation-Assisted KD-Trees
Kaiming He and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2012
paper   poster

A Global Sampling Method for Alpha Matting
Kaiming He, Christoph Rhemann, Carsten Rother, Xiaoou Tang, and Jian Sun
Computer Vision and Pattern Recognition (CVPR), 2011
paper

Guided Image Filtering
Kaiming He, Jian Sun, and Xiaoou Tang
European Conference on Computer Vision (ECCV), 2010 (Oral)
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2012
paper   PAMI version   supp   code   slides   project

Fast Matting using Large Kernel Matting Laplacian Matrices
Kaiming He, Jian Sun, and Xiaoou Tang
Computer Vision and Pattern Recognition (CVPR), 2010
paper   supp

Single Image Haze Removal using Dark Channel Prior
Kaiming He, Jian Sun, and Xiaoou Tang
Computer Vision and Pattern Recognition (CVPR), 2009 (Oral). CVPR Best Paper Award
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted in 2010
paper   PAMI version   images   slides   videos   project   thesis