Fast matting using large kernel matting Laplacian matrices. - Kaiming He; Jian Sun 001; Xiaoou Tang (CVPR, 2010)

A global sampling method for alpha matting. - Kaiming He; Christoph Rhemann; Carsten Rother; Xiaoou Tang; Jian Sun 001 (CVPR, 2011)

Single Image Haze Removal Using Dark Channel Prior. - Kaiming He; Jian Sun 001; Xiaoou Tang (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Computing nearest-neighbor fields via Propagation-Assisted KD-Trees. - Kaiming He; Jian Sun 001 (CVPR, 2012)

Statistics of Patch Offsets for Image Completion. - Kaiming He; Jian Sun 001 (ECCV (2), 2012)

Optimized Product Quantization for Approximate Nearest Neighbor Search. - Tiezheng Ge; Kaiming He; Qifa Ke; Jian Sun 001 (CVPR, 2013)

K-Means Hashing: An Affinity-Preserving Quantization Method for Learning Binary Compact Codes. - Kaiming He; Fang Wen 001; Jian Sun 001 (CVPR, 2013)

Content-Aware Rotation. - Kaiming He; Huiwen Chang; Jian Sun 001 (ICCV, 2013)

Constant Time Weighted Median Filtering for Stereo Matching and Beyond. - Ziyang Ma 002; Kaiming He; Yichen Wei; Jian Sun 001; Enhua Wu (ICCV, 2013)

Joint Inverted Indexing. - Yan Xia; Kaiming He; Fang Wen 001; Jian Sun 001 (ICCV, 2013)

Guided Image Filtering. - Kaiming He; Jian Sun 001; Xiaoou Tang (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Rectangling panoramic images via warping. - Kaiming He; Huiwen Chang; Jian Sun 001 (ACM Trans. Graph., 2013)

Product Sparse Coding. - Tiezheng Ge; Kaiming He; Jian Sun 001 (CVPR, 2014)

Learning a Deep Convolutional Network for Image Super-Resolution. - Chao Dong 005; Chen Change Loy; Kaiming He; Xiaoou Tang (ECCV (4), 2014)

Graph Cuts for Supervised Binary Coding. - Tiezheng Ge; Kaiming He; Jian Sun 001 (ECCV (7), 2014)

Optimized Product Quantization. - Tiezheng Ge; Kaiming He; Qifa Ke; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Image Completion Approaches Using the Statistics of Similar Patches. - Kaiming He; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Convolutional feature masking for joint object and stuff segmentation. - Jifeng Dai; Kaiming He; Jian Sun 001 (CVPR, 2015)

Convolutional neural networks at constrained time cost. - Kaiming He; Jian Sun 001 (CVPR, 2015)

A geodesic-preserving method for image warping. - Dongping Li; Kaiming He; Jian Sun 001; Kun Zhou (CVPR, 2015)

Sparse projections for high-dimensional binary codes. - Yan Xia; Kaiming He; Pushmeet Kohli; Jian Sun 001 (CVPR, 2015)

Efficient and accurate approximations of nonlinear convolutional networks. - Xiangyu Zhang 005; Jianhua Zou; Xiang Ming; Kaiming He; Jian Sun 001 (CVPR, 2015)

BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation. - Jifeng Dai; Kaiming He; Jian Sun 001 (ICCV, 2015)

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. - Kaiming He; Xiangyu Zhang 005; Shaoqing Ren; Jian Sun 001 (ICCV, 2015)

Fast Guided Filter. - Kaiming He; Jian Sun 001 (CoRR, 2015)

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. - Kaiming He; Xiangyu Zhang 005; Shaoqing Ren; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Instance-Aware Semantic Segmentation via Multi-task Network Cascades. - Jifeng Dai; Kaiming He; Jian Sun 001 (CVPR, 2016)

Deep Residual Learning for Image Recognition. - Kaiming He; Xiangyu Zhang 005; Shaoqing Ren; Jian Sun 001 (CVPR, 2016)

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation. - Di Lin 002; Jifeng Dai; Jiaya Jia; Kaiming He; Jian Sun 001 (CVPR, 2016)

Instance-Sensitive Fully Convolutional Networks. - Jifeng Dai; Kaiming He; Yi Li 038; Shaoqing Ren; Jian Sun 001 (ECCV (6), 2016)

Identity Mappings in Deep Residual Networks. - Kaiming He; Xiangyu Zhang 005; Shaoqing Ren; Jian Sun 001 (ECCV (4), 2016)

Is Faster R-CNN Doing Well for Pedestrian Detection? - Liliang Zhang; Liang Lin; Xiaodan Liang; Kaiming He (ECCV (2), 2016)

R-FCN: Object Detection via Region-based Fully Convolutional Networks. - Jifeng Dai; Yi Li 038; Kaiming He; Jian Sun 001 (NIPS, 2016)

Image Super-Resolution Using Deep Convolutional Networks. - Chao Dong 005; Chen Change Loy; Kaiming He; Xiaoou Tang (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Accelerating Very Deep Convolutional Networks for Classification and Detection. - Xiangyu Zhang 005; Jianhua Zou; Kaiming He; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Feature Pyramid Networks for Object Detection. - Tsung-Yi Lin; Piotr Dollár; Ross B. Girshick; Kaiming He; Bharath Hariharan; Serge J. Belongie (CVPR, 2017)

Aggregated Residual Transformations for Deep Neural Networks. - Saining Xie; Ross B. Girshick; Piotr Dollár; Zhuowen Tu; Kaiming He (CVPR, 2017)

Transitive Invariance for Self-Supervised Visual Representation Learning. - Xiaolong Wang 004; Kaiming He; Abhinav Gupta 001 (ICCV, 2017)

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour. - Priya Goyal; Piotr Dollár; Ross B. Girshick; Pieter Noordhuis; Lukasz Wesolowski; Aapo Kyrola; Andrew Tulloch; Yangqing Jia; Kaiming He (CoRR, 2017)

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. - Shaoqing Ren; Kaiming He; Ross B. Girshick; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Object Detection Networks on Convolutional Feature Maps. - Shaoqing Ren; Kaiming He; Ross B. Girshick; Xiangyu Zhang 005; Jian Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Non-Local Neural Networks. - Xiaolong Wang 004; Ross B. Girshick; Abhinav Gupta 001; Kaiming He (CVPR, 2018)

Detecting and Recognizing Human-Object Interactions. - Georgia Gkioxari; Ross B. Girshick; Piotr Dollár; Kaiming He (CVPR, 2018)

Learning to Segment Every Thing. - Ronghang Hu; Piotr Dollár; Kaiming He; Trevor Darrell; Ross B. Girshick (CVPR, 2018)

Data Distillation: Towards Omni-Supervised Learning. - Ilija Radosavovic; Piotr Dollár; Ross B. Girshick; Georgia Gkioxari; Kaiming He (CVPR, 2018)

Exploring the Limits of Weakly Supervised Pretraining. - Dhruv Mahajan 001; Ross B. Girshick; Vignesh Ramanathan; Kaiming He; Manohar Paluri; Yixuan Li 001; Ashwin Bharambe; Laurens van der Maaten (ECCV (2), 2018)

GLoMo: Unsupervised Learning of Transferable Relational Graphs. - Zhilin Yang 001; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (NeurIPS, 2018)

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. - Zhilin Yang 001; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (CoRR, 2018)

Panoptic Feature Pyramid Networks. - Alexander Kirillov; Ross B. Girshick; Kaiming He; Piotr Dollár (CVPR, 2019)

Panoptic Segmentation. - Alexander Kirillov; Kaiming He; Ross B. Girshick; Carsten Rother; Piotr Dollár (CVPR, 2019)

Long-Term Feature Banks for Detailed Video Understanding. - Chao-Yuan Wu; Christoph Feichtenhofer; Haoqi Fan 001; Kaiming He; Philipp Krähenbühl; Ross B. Girshick (CVPR, 2019)

Feature Denoising for Improving Adversarial Robustness. - Cihang Xie; Yuxin Wu; Laurens van der Maaten; Alan L. Yuille; Kaiming He (CVPR, 2019)

TensorMask: A Foundation for Dense Object Segmentation. - Xinlei Chen; Ross B. Girshick; Kaiming He; Piotr Dollár (ICCV, 2019)

SlowFast Networks for Video Recognition. - Christoph Feichtenhofer; Haoqi Fan 001; Jitendra Malik; Kaiming He (ICCV, 2019)

Rethinking ImageNet Pre-Training. - Kaiming He; Ross B. Girshick; Piotr Dollár (ICCV, 2019)

Deep Hough Voting for 3D Object Detection in Point Clouds. - Charles R. Qi; Or Litany; Kaiming He; Leonidas J. Guibas (ICCV, 2019)

Exploring Randomly Wired Neural Networks for Image Recognition. - Saining Xie; Alexander Kirillov; Ross B. Girshick; Kaiming He (ICCV, 2019)

Momentum Contrast for Unsupervised Visual Representation Learning. - Kaiming He; Haoqi Fan 001; Yuxin Wu; Saining Xie; Ross B. Girshick (CVPR, 2020)

PointRend: Image Segmentation As Rendering. - Alexander Kirillov; Yuxin Wu; Kaiming He; Ross B. Girshick (CVPR, 2020)

Designing Network Design Spaces. - Ilija Radosavovic; Raj Prateek Kosaraju; Ross B. Girshick; Kaiming He; Piotr Dollár (CVPR, 2020)

A Multigrid Method for Efficiently Training Video Models. - Chao-Yuan Wu; Ross B. Girshick; Kaiming He; Christoph Feichtenhofer; Philipp Krähenbühl (CVPR, 2020)

Are Labels Necessary for Neural Architecture Search? - Chenxi Liu 001; Piotr Dollár; Kaiming He; Ross B. Girshick; Alan L. Yuille; Saining Xie (ECCV (4), 2020)

Graph Structure of Neural Networks. - Jiaxuan You; Jure Leskovec; Kaiming He; Saining Xie (ICML, 2020)

Improved Baselines with Momentum Contrastive Learning. - Xinlei Chen; Haoqi Fan 001; Ross B. Girshick; Kaiming He (CoRR, 2020)

Group Normalization. - Yuxin Wu; Kaiming He (Int. J. Comput. Vis., 2020)

Mask R-CNN. - Kaiming He; Georgia Gkioxari; Piotr Dollár; Ross B. Girshick (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Focal Loss for Dense Object Detection. - Tsung-Yi Lin; Priya Goyal; Ross B. Girshick; Kaiming He; Piotr Dollár (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Exploring Simple Siamese Representation Learning. - Xinlei Chen; Kaiming He (CVPR, 2021)

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning. - Christoph Feichtenhofer; Haoqi Fan 001; Bo Xiong; Ross B. Girshick; Kaiming He (CVPR, 2021)

An Empirical Study of Training Self-Supervised Vision Transformers. - Xinlei Chen; Saining Xie; Kaiming He (ICCV, 2021)

Benchmarking Detection Transfer Learning with Vision Transformers. - Yanghao Li; Saining Xie; Xinlei Chen; Piotr Dollár; Kaiming He; Ross B. Girshick (CoRR, 2021)

Masked Autoencoders Are Scalable Vision Learners. - Kaiming He; Xinlei Chen; Saining Xie; Yanghao Li; Piotr Dollár; Ross B. Girshick (CVPR, 2022)

Exploring Plain Vision Transformer Backbones for Object Detection. - Yanghao Li; Hanzi Mao; Ross B. Girshick; Kaiming He (ECCV (9), 2022)

Masked Autoencoders As Spatiotemporal Learners. - Christoph Feichtenhofer; Haoqi Fan 001; Yanghao Li; Kaiming He (NeurIPS, 2022)

POI recommendation based on a multiple bipartite graph network model. - Chen Lang; Ze Wang 016; Kaiming He; Shimin Sun (J. Supercomput., 2022)

Scaling Language-Image Pre-Training via Masking. - Yanghao Li; Haoqi Fan 001; Ronghang Hu; Christoph Feichtenhofer; Kaiming He (CVPR, 2023)

Self-conditioned Image Generation via Generating Representations. - Tianhong Li; Dina Katabi; Kaiming He (CoRR, 2023)

Physically Compatible 3D Object Modeling from a Single Image. - Minghao Guo; Bohan Wang; Pingchuan Ma 002; Tianyuan Zhang; Crystal Elaine Owens; Chuang Gan 001; Josh Tenenbaum 001; Kaiming He; Wojciech Matusik (NeurIPS, 2024)

Return of Unconditional Generation: A Self-supervised Representation Generation Method. - Tianhong Li; Dina Katabi; Kaiming He (NeurIPS, 2024)

Autoregressive Image Generation without Vector Quantization. - Tianhong Li; Yonglong Tian; He Li; Mingyang Deng; Kaiming He (NeurIPS, 2024)

Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers. - Lirui Wang; Xinlei Chen; Jialiang Zhao; Kaiming He (NeurIPS, 2024)

Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning. - Linsen Li; Pratyush Anand; Kaiming He; Dirk R. Englund (CoRR, 2024)

Transformers without Normalization. - Jiachen Zhu 002; Xinlei Chen; Kaiming He; Yann LeCun; Zhuang Liu 003 (CVPR, 2025)

A Decade's Battle on Dataset Bias: Are We There Yet? - Zhuang Liu 003; Kaiming He (ICLR, 2025)

Deconstructing Denoising Diffusion Models for Self-Supervised Learning. - Xinlei Chen; Zhuang Liu 003; Saining Xie; Kaiming He (ICLR, 2025)

Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens. - Lijie Fan; Tianhong Li; Siyang Qin; Yuanzhen Li; Chen Sun 002; Michael Rubinstein; Deqing Sun; Kaiming He; Yonglong Tian (ICLR, 2025)

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes. - Minghao Guo; Bohan Wang; Kaiming He; Wojciech Matusik (ICLR, 2025)

Is Noise Conditioning Necessary for Denoising Generative Models? - Qiao Sun; Zhicheng Jiang; Hanhong Zhao; Kaiming He (CoRR, 2025)

Fractal Generative Models. - Tianhong Li; Qinyi Sun; Lijie Fan; Kaiming He (CoRR, 2025)

Denoising Hamiltonian Network for Physical Reasoning. - Congyue Deng; Brandon Y. Feng; Cecilia Garraffo; Alan Garbarz; Robin Walters 001; William T. Freeman; Leonidas J. Guibas; Kaiming He (CoRR, 2025)

Mean Flows for One-step Generative Modeling. - Zhengyang Geng; Mingyang Deng; Xingjian Bai; J. Zico Kolter; Kaiming He (CoRR, 2025)

Diffuse and Disperse: Image Generation with Representation Regularization. - Runqian Wang; Kaiming He (CoRR, 2025)