Gao Huang


Bio

Gao Huang is an Associate Professor affiliated with the Department of Automation at Tsinghua University. He obtained the PhD degree in machine learning from Tsinghua in 2015, and spent three years at Cornell University as a postdoc. His research interests lie in machine learning and computer vision. In particular, he is actively working on efficient deep learning, dynamic neural networks, learning with limited data and reinforcement learning. His work on DenseNet won the Best Paper Award of CVPR (2017) and has collected more than 55,000 citations according to Google Scholar. (C.V.)

For students who are interested in joining our lab (PhD/Mater/Intern/Postdoc), please contact me via gaohuang AT tsinghua.edu.cn. For international students, please check HERE for available scholarships. For postdocs, please check HERE.


Selected Recent Journal Papers (Google Scholar)

Convolution-enhanced Evolving Attention Networks. [code]
Yujing Wang, Yaming Yang, Zhuo Li, Jiangang Bai, Mingliang Zhang, Xiangtai Li, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023.

SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation. [code]
Binhui Xie, Shuang Li, Mingjia Li, Chi Harold Liu, Gao Huang, Guoren Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023.

Glance and Focus Networks for Dynamic Visual Recognition. [code]
Gao Huang*, Yulin Wang*, Kangchen Lv, Haojun Jiang, Wenhui Huang, Pengfei Qi, Shiji Song.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022.

Dynamic Neural Networks: A Survey.
Yizeng Han*,Gao Huang*, Shiji Song, Le Yang, Honghui Wang, Yulin Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021.

Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning.
Wenjie Shi, Gao Huang, Shiji Song, Cheng Wu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021.

Generalized Domain Conditioned Adaptation Network. [code]
Shuang Li, Binhui Xie, Qiuxia Lin, Chi Harold Liu, Gao Huang, Guoren Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021.

Regularizing Deep Networks with Semantic Data Augmentation. [code]
Yulin Wang*, Gao Huang*, Shiji Song, Xuran Pan, Yitong Xia, Cheng Wu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021.

Self-Supervised Discovering of Interpretable Features for Reinforcement Learning. [code]
Wenjie Shi, Gao Huang, Shiji Song, Zhuoyuan Wang, Tingyu Lin, Cheng Wu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2020.

Deep Residual Correction Network for Partial Domain Adaptation.
Shuang Li, Chi Harold Liu, Qiuxia Lin, Qi Wen, Limin Su, Gao Huang, Zhengming Ding.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2019.

Convolutional Networks with Dense Connectivity. [code]
Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens Van Der Maaten, Kilian Q. Weingerger.
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) 2019.

(Journal version of DenseNet; Deep understanding of dense connectivity.)



* Equal Contribution.



Selected Recent Conference Papers (Google Scholar)

FLatten Transformer: Vision Transformer using Focused Linear Attention. [code]
Dongchen Han*, Xuran Pan*, Yizeng Han, Shiji Song, Gao Huang.
International Conference on Computer Vision (ICCV) 2023.

Dynamic Perceiver for Efficient Visual Recognition. [code]
Yizeng Han*, Dongchen Han*, Zeyu Liu, Yulin Wang, Xuran Pan, Yifan Pu, Chao Deng, Junlan Feng, Shiji Song, Gao Huang.
International Conference on Computer Vision (ICCV) 2023.

EfficientTrain: Exploring Generalized Curriculum Learning for Training Visual Backbones. [code]
Yulin Wang*, Yang Yue*, Rui Lu, Tianjiao Liu, Zhao Zhong, Shiji Song, Gao Huang.
International Conference on Computer Vision (ICCV) 2023.

Adaptive Rotated Convolution for Rotated Object Detection. [code]
Yifan Pu*, Yiru Wang*, Zhuofan Xia, Yizeng Han, Yulin Wang, Weihao Gan, Zidong Wang, Shiji Song, Gao Huang.
International Conference on Computer Vision (ICCV) 2023.

Deep Incubation: Training Large Models by Divide-and-Conquering. [code]
Zanlin Ni*, Yulin Wang*, Jiangwei Yu, Haojun Jiang, Yue Cao, Gao Huang.
International Conference on Computer Vision (ICCV) 2023.

Boosting Offline Reinforcement Learning with Action Preference Query.
Qisen Yang*, Shenzhi Wang*, Matthieu Gaetan Lin, Shiji Song, Gao Huang.
International Conference on Machine Learning (ICML) 2023.

Zero-shot Generative Model Adaptation via Image-specific Prompt Learning. [code]
Jiayi Guo*, Chaofei Wang*, You Wu, Eric Zhang, Kai Wang, Xingqian Xu, Shiji Song, Humphrey Shi, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023.

Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention. [code]
Xuran Pan*, Tianzhu Ye*, Zhuofan Xia, Shiji Song, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023.

Budgeted Training for Vision Transformer.
Zhuofan Xia*, Xuran Pan*, Xuan Jin*, Yuan He, Hui Xue, Shiji Song, Gao Huang.
International Conference on Learning Representations (ICLR) 2023.

Efficient Knowledge Distillation from Model Checkpoints. [code]
Chaofei Wang*, Qisen Yang*, Rui Huang, Shiji Song, Gao Huang.
Neural Information Processing Systems (NeurIPS Spotlight) 2022.

Provable General Function Class Representation Learning in Multitask Bandits and MDP.
Rui Lu, Andrew Zhao, Simon Shaolei Du, Gao Huang.
Neural Information Processing Systems (NeurIPS Spotlight) 2022.

Latency-aware Spatial-wise Dynamic Networks. [code]
Yizeng Han*, Zhihang Yuan*, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2022.

A Mixture Of Surprises for Unsupervised Reinforcement Learning. [code]
Andrew Zhao*, Matthieu Gaetan Lin*, Yangguang Li, Yong-jin Liu, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2022.

Contrastive Language-Image Pre-Training with Knowledge Graphs.
Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2022.

AdaFocus V3: On Unified Spatial-temporal Dynamic Video Recognition.
Yulin Wang*, Yang Yue*, Xinhong Xu, Ali Hassani, Victor Kulikov, Nikita Orlov, Shiji Song, Humphrey Shi, Gao Huang.
European Conference on Computer Vision (ECCV) 2022.

Learning to Weight Samples for Dynamic Early-exiting Networks. [code]
Yizeng Han*, Yifan Pu*, Zihang Lai, Chaofei Wang, Shiji Song, Junfeng Cao, Wenhui Huang, Chao Deng, Gao Huang.
European Conference on Computer Vision (ECCV) 2022.

ActiveNeRF: Learning where to See with Uncertainty Estimation. [code]
Xuran Pan, Zihang Lai, Shiji Song, Gao Huang.
European Conference on Computer Vision (ECCV) 2022.

Pseudo-Q: Generating Pseudo Language Queries for Visual Grounding. [code]
Haojun Jiang*, Yuanze Lin*, Dongchen Han, Shiji Song, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

On the Integration of Self-Attention and Convolution. [code]
Xuran Pan, Chunjiang Ge, Rui Lu, Shiji Song, Guanfu Chen, Zeyi Huang, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

Exploring the Equivalence of Siamese Self-Supervised Learning via A Unified Gradient Framework. [code]
Chenxin Tao*, Honghui Wang*, Xizhou Zhu, Jiahua Dong, Shiji Song, Gao Huang, Jifeng Dai.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition. [code]
Yulin Wang*, Yang Yue*, Yuanze Lin, Haojun Jiang, Zihang Lai, Victor Kulikov, Nikita Orlov, Humphrey Shi, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

Vision Transformer with Deformable Attention. [code]
Zhuofan Xia*, Xuran Pan*, Shiji Song, Li Erran Li, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR Best Paper Finalist) 2022.

Assessing a Single Image in Reference-Guided Image Synthesis.
Jiayi Guo, Chaoqun Du, Jiangshan Wang, Huijuan Huang, Pengfei Wan, Gao Huang.
AAAI Conference on Artificial Intelligence (AAAI Oral) 2021.

Searching Parameterized AP Loss for Object Detection. [code]
Chenxin Tao*, Zizhang Li*, Xizhou Zhu*, Gao Huang, Yong Liu, Jifeng Dai.
Neural Information Processing Systems (NeurIPS) 2021.

Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length. [code]
Yulin Wang*, Rui Huang*, Shiji Song, Zeyi Huang, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2021.

Adaptive Focus for Efficient Video Recognition. [code]
Yulin Wang*, Zhaoxi Chen*, Haojun Jiang, Shiji Song, Yizeng Han, Gao Huang.
International Conference on Computer Vision (ICCV Oral) 2021.

Towards Learning Spatially Discriminative Feature Representations.
Chaofei Wang*, Jiayu Xiao*, Yizeng Han, Qisen Yang, Shiji Song, Gao Huang.
International Conference on Computer Vision (ICCV) 2021.

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving.
Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng, Yixuan Li, Gao Huang.
International Conference on Computer Vision (ICCV) 2021.

Evolving Attention with Residual Convolutions.
Yujing Wang*, Yaming Yang*, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong.
International Conference on Machine Learning (ICML) 2021.

3D Object Detection with Pointformer. [code]
Xuran Pan*, Zhuofan Xia*, Shiji Song, Li Erran Li, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

CondenseNet V2: Sparse Feature Reactivation for Deep Networks. [code]
Le Yang*, Haojun Jiang*, Ruojin Cai, Yulin Wang, Shiji Song, Gao Huang, Qi Tian.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

Cross-iteration Batch Normalization. [code]
Zhuliang Yao, Yue Cao, Shuxin Zheng, Gao Huang, Stephen Lin.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

Revisiting Locally Supervised Learning: an Alternative to End-to-end Training. [code]
Yulin Wang, Zanlin Ni, Shiji Song, Le Yang, Gao Huang.
International Conference on Learning Representations (ICLR) 2021.

Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation.
Hao Li*, Chenxin Tao*, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai.
International Conference on Learning Representations (ICLR) 2021.

Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification. [code]
Yulin Wang, Kangchen Lv, Rui Huang, Shiji Song, Le Yang, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2020.

Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation. [code]
Zhenda Xie, Zheng Zhang, Xizhou Zhu, Gao Huang , Stephen Lin.
European Conference on Computer Vision (ECCV Oral) 2020.

Resolution Adaptive Networks for Efficient Inference. [code]
Le Yang*, Yizeng Han*, Xi Chen*, Shiji Song, Jifeng Dai, Gao Huang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

Asymmetric Valleys: Beyond Sharp and Flat Local Minima. [code] [slides]
Haowei He, Gao Huang, Yang Yuan.
Neural Information Processing Systems (NeurIPS Spotlight) 2019.
Implicit Semantic Data Augmentation for Deep Networks . [code]
Yulin Wang*, Xuran Pan*, Shiji Song, Hong Zhang, Cheng Wu, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2019.

Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning. [code] [poster]
Wenjie Shi, Shiji Song, Hui Wu, Ya-Chu Hsu, Cheng Wu, Gao Huang.
Neural Information Processing Systems (NeurIPS) 2019.
Improved Techniques for Training Adaptive Deep Networks. [code]
Hao Li*, Hong Zhang*, Xiaojuan Qi, Ruigang Yang, Gao Huang.
International Conference on Computer Vision (ICCV) 2019.

Rethinking the Value of Network Pruning. [code]
Zhuang Liu*, Mingjie Sun*, Tinghui, Zhou, Gao Huang, Trevor Darrell.
International Conference on Learning Representations (ICLR) 2019.
Anytime Stereo Image Depth Estimation on Mobile Devices.
Yan Wang, Zihang Lai, Gao Huang, Brian Wang, Laurens van der Maaten, Mark Campbell, Kilian Q. Weinberger.
International Conference on Robotics and Automation (ICRA) 2019.
Horizontal Pyramid Matching for Person Re-identification.
Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang.
AAAI Conference on Artificial Intelligence (AAAI) 2019.
An Empirical Study on Evaluation Metrics of Generative Adversarial Networks. [code]
Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Weinberger.
arXiv Preprint 2018.
CondenseNet: An Efficient DenseNet using Learned Group Convolutions. [code] [talk]
Gao Huang*, Shichen Liu*, Laurens van der Maaten, Kilian Q. Weinberger.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR Spotlight) 2018.

Resource Aware Person Re-identification across Multiple Resolutions. [code]
Yan Wang*, Lequn Wang*, Yurong You*, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Weinberger.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.

Multi-Scale Dense Convolutional Networks for Resource Efficient Image Classification. [code]
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger.
International Conference on Learning Representations (ICLR Oral) 2018.

Memory-Efficient Implementation of DenseNets. [code1] [code2]
Geoff Pleiss*, Danlu Chen*, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger.
Technical Report 2017.
Learning Efficient Convolutional Networks through Network Slimming. [code]
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang.
International Conference on Computer Vision (ICCV) 2017.

Densely Connected Convolutional Networks. [code] [talk] [slides]
Gao Huang*, Zhuang Liu*, Laurens van der Maaten, Kilian Weinberger.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR Best Paper) 2017.

Snapshot Ensembles: Train 1, Get M for Free. [code]
Gao Huang*, Yixuan Li*, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Weinberger.
International Conference on Learning Representations (ICLR) 2017.
Supervised Word Mover's Distance. [code] [talk]
Gao Huang*, Chuan Guo*, Matt Kusner, Yu Sun, Fei Sha, Kilian Weinberger.
Neural Information Processing Systems (NIPS Oral) 2016.

Deep Networks with Stochastic Depth.
[code] [poster] [talk]
Gao Huang*, Yu Sun*, Zhuang Liu, Daniel Sedra, Kilian Weinberger.
European Conference on Computer Vision (ECCV Spotlight) 2016.

(This paper was recommended as an Oral at NIPS 2016 Deep Learning Symposium)



* Equal Contribution.



Awards

  • CVPR Best Paper Finalists, 2022
  • AI 2000 Most Influential Scholar in Computer Vision, AMiner, 2022
  • MIT TR 35 Asia-Pacific, MIT Technology Review, 2021
  • Research Fund for Outstanding Young Scholars, Nature Science Foundation of China, 2020
  • DAMO Qingcheng Award, Alibaba, 2020
  • Outstanding Young Researcher Award, Chinese Association for Artificial Intelligence, 2019
  • Zhiyuan Young Scholar, Beijing Academy of Artificial Intelligence (BAAI), 2019
  • First Prize of Nature Science Award, Chinese Association for Artificial Intelligence, 2018
  • Super AI Leader - Pioneer Award, World AI Conference (WAIC), 2018
  • NeurIPS Workshop Best Paper Award, 2018
  • CVPR Best Paper Award, 2017
  • Doctoral Dissertation Award, Chinese Association of Automation, 2015

Students

Professional Activities

  • Associate Editor, IEEE Transactions on Pattern Analysis and Machine Intelligence (2023-).
  • Associate Editor, IEEE Transactions on Big Data (2021-).
  • Associate Editor, Pattern Recognition (2022-).
  • Area Chair of NeurIPS(2023, 2022), ICCV(2023), ICML(2022), UAI(2022), CVPR(2021).
  • Senior Program Committee (SPC) member of AAAI (2018, 2020), IJCAI (2021).
  • Reviewer for JMLR, TPAMI, IJCV, Machine Learning, IJCV, TIP, TKDE, TNNLS, ...
  • Reviewer for NeurIPS, ICML, CVPR, ICCV, ECCV, AAAI, AISTATS, ...

Contact

  • gaohuang at tsinghua dot edu dot cn
  • 617A Centre Main Building, Tsinghua University, Beijing 100084, China.