Currently, he is a research fellow at mmlab, Nanyang Technological University (NTU) Singapore, working with Prof. Ziwei Liu. Prior to this, he worked as a Research Scientist at the Sea AI Lab of Sea Group.
He completed Ph.D. degree in 2021 at CASIA, supervised by Prof. Tieniu Tan, co-supervised by Prof. Liang Wang and Prof. Wei Wang. He was a visting student from Sep, 2019 to Sep, 2020 in Learning and Vision Lab at National University of Singapore, working with Prof. Jiashi FENG.
His research lies at the intersection of deep learning and computer vision, including vision-based human perception (pose and action), few-shot learning, self-supervised learning, semi-supervised learning, in-context learning and video generation.
Remote cooperations are welcome (ChenYang.Si.Mail@gmail.com).
Contact
- Email:
- ChenYang.Si.Mail@gmail.com
- chenyang.si@ntu.edu.sg
sicy@sea.comchenyang.si@cripac.ia.ac.cn
Publications
Semantic Prompt for Few-Shot Learning
Wentao Chen*, Chenyang Si*, Zhang Zhang, Liang Wang, Zilei Wang, Tieniu Tan
(CVPR), 2023
[pdf] [code] [video]Metaformer baselines for vision
Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang
Tech report, 2022
[pdf] [code]Federated Zero-Shot Learning with Mid-Level Semantic Knowledge Transfer
Shitong Sun, Chenyang Si, Shaogang Gong, Guile Wu
Tech report, 2022
[pdf]Mugs: A Multi-Granular Self-Supervised Learning Framework
Pan Zhou, Yichen Zhou, Chenyang Si, Weihao Yu, Teck Khim Ng, Shuicheng Yan
NeurIPS Workshop, 2022
[pdf] [code]Transformed Autoencoder: Pre-training with Mask-Free Encoder and Transformed Decoder
Yichen Zhou, Pan Zhou, Chenyang Si, Weihao Yu, Teck Khim Ng, Shuicheng YAN
NeurIPS Workshop, 2022
[[pdf]]Inception Transformer
Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang, Shuicheng Yan
(NeurIPS, Oral), 2022
[pdf] [code]Contrast-reconstruction Representation Learning for Self-supervised Skeleton-based Action Recognition
Peng Wang, Jun Wen, Chenyang Si, Yuntao Qian, Liang Wang
(TIP), 2022
[pdf]Metaformer is actually what you need for vision
Weihao Yu, Mi Luo, Pan Zhou, Chenyang Si, Yichen Zhou, Xinchao Wang, Jiashi Feng, Shuicheng Yan
(CVPR), 2022
[pdf] [code]Generalizable Person Re-Identification via Self-Supervised Batch Norm Test-Time Adaption
Ke Han, Chenyang Si, Yan Huang, Liang Wang, Tieniu Tan
(AAAI), 2022
[pdf]Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images
Wentao Chen, Chenyang Si, Wei Wang, Liang Wang, Zilei Wang, Tieniu Tan
(IJCAI), 2021
[[pdf]]Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
Chenyang Si, Xuecheng Nie, Wei Wang, Liang Wang, Tieniu Tan, Jiashi Feng
(ECCV), 2020
[pdf] [video]Unsupervised Motion Representation Learning from Skeleton Sequence via Neighbor Reconstruction
Chenyang Si, Wei Wang, Liang Wang, Tieniu Tan, Jiashi FengSkeleton-Based Action Recognition with Hierarchical Spatial Reasoning and Temporal Stack Learning Network
Chenyang Si, Ya Jing, Wei Wang, Liang Wang, Tieniu Tan
(Pattern Recognition), 2020
[pdf]Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search
Ya Jing, Chenyang Si, Junbo Wang, Wei Wang, Liang Wang, Tieniu Tan
(AAAI), oral, 2020
[pdf]An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, Tieniu Tan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
[pdf]Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning
Chenyang Si, Ya Jing, Wei Wang, Liang Wang, Tieniu Tan
European Conference on Computer Vision (ECCV), 2018
[pdf]Pose-Based Two-Stream Relational Networks for Action Recognition in Videos
Wei Wang, Jinjin Zhang, Chenyang Si, Liang Wang
(arxiv), 2018
[pdf]Multistage adversarial losses for pose-based human image synthesis
Chenyang Si, Wei Wang, Liang Wang, Tieniu Tan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR,), spotlight, 2018
[pdf]
Teaching Experience
- Teaching Assistant
Deep Learning
Mar. 2019-Jun. 2019
University of Chinese Academy of Sciences