Author

Gao Huang

Associate Professor, Tsinghua University - Cited by 53,253 - Machine Learning - Computer Vision - Dynamic Neural Networks - Efficient Deep Learning

Biography

Dr. Gao Huang is an Assistant Professor in the Key Laboratory of Biomimetic Robots and Systems, Beijing Institute of Technology, Beijing 100081, China. His research interest includes Speech Science, Hearing Science, etc. He has published more than 39 publications and the articles are informative and got good citations.
Title
Cited by
Year
Dynamic neural networks: A survey
Y Han, G Huang, S Song, L Yang, H Wang, Y WangIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021202
300
2021
Vision Transformer with Deformable Attention
Z Xia, X Pan, S Song, LE Li, G HuangIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022202
140
2022
Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length
Y Wang, R Huang, S Song, Z Huang, G HuangNeural Information Processing Systems (NeurIPS), 2021113202
113
2021
On the Integration of Self-Attention and Convolution
X Pan, C Ge, R Lu, S Song, G Chen, Z Huang, G HuangIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022202
102
2022
Adaptive Focus for Efficient Video Recognition
Y Wang, Z Chen, H Jiang, S Song, Y Han, G HuangInternational Conference on Computer Vision (ICCV), 2021202
51
2021
Sepico: Semantic-guided pixel contrast for domain adaptive semantic segmentation
B Xie, S Li, M Li, CH Liu, G Huang, G WangIEEE Transactions on Pattern Analysis and Machine Intelligence, 2023202
44
2023
Domain adaptation via prompt learning
C Ge, R Huang, M Xie, Z Lai, S Song, S Li, G HuangarXiv preprint arXiv:2202.06687, 2022202
40
2022
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
Y Yang, X Ma, C Li, Z Zheng, Q Zhang, G Huang, J Yang, Q ZhaoNeural Information Processing Systems (NeurIPS), 2021202
37
2021
Siamese image modeling for self-supervised vision representation learning
C Tao, X Zhu, W Su, G Huang, B Li, J Zhou, Y Qiao, X Wang, J DaiProceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023202
34
2023
CondenseNet V2: Sparse Feature Reactivation for Deep Networks
L Yang, H Jiang, R Cai, Y Wang, S Song, G Huang, Q TianIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021202
32
2021
Exploring the Equivalence of Siamese Self-Supervised Learning via A Unified Gradient Framework
C Tao, H Wang, X Zhu, J Dong, S Song, G Huang, J DaiIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022202
29
2022
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
Y Wang, Y Yue, Y Lin, H Jiang, Z Lai, V Kulikov, N Orlov, H Shi, G HuangIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022202
27
2022
Pseudo-Q: Generating Pseudo Language Queries for Visual Grounding
H Jiang, Y Lin, D Han, S Song, G HuangIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 202
22
2022
Autoloss-zero: Searching loss functions from scratch for generic tasks
H Li, T Fu, J Dai, H Li, G Huang, X ZhuIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022202
17
2022
Evolving attention with residual convolutions
Y Wang, Y Yang, J Bai, M Zhang, J Bai, J Yu, C Zhang, G Huang, Y TongInternational Conference on Machine Learning （ICML）, 2021202
17
2021
Spatially adaptive feature refinement for efficient inference
Y Han, G Huang, S Song, L Yang, Y Zhang, H JiangIEEE Transactions on Image Processing 30, 9345-9358, 2021202
13
2021
Towards Learning Spatially Discriminative Feature Representations
C Wang, J Xiao, Y Han, Q Yang, S Song, G HuangInternational Conference on Computer Vision (ICCV), 1326-1335, 2021202
12
2021
Integrating large circular kernels into cnns through neural architecture search
K He, C Li, Y Yang, G Huang, JE HopcroftarXiv preprint arXiv:2107.02451, 20219202
9
2021
Contrastive Language-Image Pre-Training with Knowledge Graphs
X Pan, T Ye, D Han, S Song, G HuangNeural Information Processing Systems (NeurIPS), 2022202
9
2022
Towards all-in-one pre-training via maximizing multi-modal mutual information
W Su, X Zhu, C Tao, L Lu, B Li, G Huang, Y Qiao, X Wang, J Zhou, J DaiProceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023202
8
2023

Referred From: https://scholar.google.com.hk/citations?user=-P9LwcgAAAAJ&hl=en

Cited by
Citations 53253
h-index 44
i10-index 76
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