Gao Huang


Bio

Gao Huang is an Assistant Professor affiliated with the Department of Automation at Tsinghua University. He obtained his 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 25,000 citations according to Google Scholar. (C.V.)

If you are interested in a position (PhD, postdoc or intern) in my lab, please contact me via gaohuang at tsinghua dot edu dot cn. For international students, please check HERE for available scholarships. For postdocs, please check HERE.

Recent Publications & Preprints (Google Scholar)

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.
arXiv Preprint, 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.

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.

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.

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.

Dynamic Neural Networks: A Survey.
Yizeng Han*,Gao Huang*, Shiji Song, Le Yang, Honghui Wang, Yulin Wang.
arXiv Preprint, 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.

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.

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.

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.)


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 Oral) 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

  • Qingcheng Award, Damo Academy of Alibaba, 2020
  • Outstanding Young Researcher, Chinese Association for Artificial Intelligence, 2019
  • 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 Big Data (2021-).
  • Senior Program Committee (SPC) member of IJCAI (2021).
  • Area Chair of CVPR (2021).
  • Senior Program Committee (SPC) member of AAAI (2018, 2020).
  • Reviewer for JMLR, Machine Learning, TPAMI, IJCV, TIP, TKDE, TNNLS, ...
  • Reviewer for NeurIPS, ICML, CVPR, ICCV, ECCV, AAAI, AISTATS, ...

Contact

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