Haoqi Fan Research Engineer Facebook AI Research E-mail: haoqifan [at] gmail [dot] com

About Me

Haoqi Fan is a Research Engineer who works at Facebook AI Research (FAIR). He graduated from the Robotics Institute of Carnegie Mellon University. His research interests lie in computer vision and deep learning.

Recent News

Apr 2021: Released PyTorchVideo - a deep learning library for video understanding research.

Jun 2020: Co-organized tutorials on Visual Recognition for Images, Video, and 3D at CVPR 2020 and ECCV 2020.

Nov 2019: Released PySlowFast codebase for video understanding research.

Nov 2019: Co-organized a tutorial on Images, Video, and 3D research and code at ICCV 2019.

June 2019: Won the 1st place of AVA video activity detection challenge at the International Challenge on Activity Recognition (ActvityNet) ICCV 2019.

June 2019: Selected as CVPR 2019 Outstanding Reviewer.

Recent Publications

Multiscale Vision Transformers Haoqi Fan, Bo Xiong, Karttikeya Mangalam, Yanghao Li, Zhicheng Yan, Jitendra Malik, Christoph Feichtenhofer Tech Report, 2021 Paper code

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

Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories Xitong Yang, Haoqi Fan, Lorenzo Torresani, Larry Davis, Heng Wang Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Paper

Multiview Pseudo-Labeling for Semi-supervised Learning from Video Bo Xiong, Haoqi Fan, Kristen Grauman, Christoph Feichtenhofer Tech Report, 2021 Paper

Improved Baselines with Momentum Contrastive Learning Xinlei Chen, Haoqi Fan, Ross Girshick, Kaiming He 2-Page Tech Report, 2020 Paper code

Momentum contrast for unsupervised visual representation learning Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (Oral) Best Paper Nomination Paper code

Slowfast networks for video recognition Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, Kaiming He International Conference on Computer Vision (ICCV), 2019 (Oral) Paper code

Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Yunpeng Chen, Haoqi Fan, Bing Xu, Zhicheng Yan, Yannis Kalantidis, Marcus Rohrbach, Shuicheng Yan, Jiashi Feng International Conference on Computer Vision (ICCV), 2019 Paper code

Order-Aware Generative Modeling Using the 3D-Craft Dataset Zhuoyuan Chen∗ , Demi Guo∗ , Tong Xiao∗ , Saining Xie, Xinlei Chen, Haonan Yu, Jonathan Gray, Kavya Srinet, Haoqi Fan, Jerry Ma, Charles R. Qi, Shubham Tulsiani, Arthur Szlam, and C. Lawrence Zitnick International Conference on Computer Vision (ICCV), 2019 Paper

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

Stacked Latent Attention for Multimodal Reasoning Haoqi Fan, Jiatong Zhou Conference on Computer Vision and Pattern Recognition (CVPR), 2018 Paper

Efficient K-Shot Learning with Regularized Deep Networks Donghyun Yoo, Haoqi Fan, Vishnu Naresh Boddeti, Kris M. Kitani Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018 Paper

Going deeper into first-person activity recognition Minghuang Ma, Haoqi Fan, Kris M. Kitani Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Paper

Open Source Projects

PySlowFast: video understanding codebase for state-of-the-art research Haoqi Fan, Yanghao Li, Wan-Yen Lo, Christoph Feichtenhofer

PyTorchVideo: A Deep Learning Library for Video Understanding Haoqi Fan *, Tullie Murrell *, Heng Wang ‡, Kalyan Vasudev Alwala‡, Yanghao Li‡, Yilei Li‡, Bo Xiong ‡, Nikhila Ravi, Meng Li, Haichuan Yang, Jitendra Malik, Ross Girshick, Matt Feiszli, Aaron Adcock†, Wan-Yen Lo†, Christoph Feichtenhofer †