activity
20182022
most citedAn Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

97 citations · 124 across the 6 of their papers we have counts for

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10 papers · 1 filter

cs.CV2022

Inception Transformer

Chenyang Si, Weihao Yu, Pan Zhou +3

Recent studies show that Transformer has strong capability of building long-range dependencies, yet is incompetent in capturing high frequencies that predominantly convey local inf…

cs.CV2022

Generalizable Person Re-Identification via Self-Supervised Batch Norm Test-Time Adaption

Ke Han, Chenyang Si, Yan Huang +2

In this paper, we investigate the generalization problem of person re-identification (re-id), whose major challenge is the distribution shift on an unseen domain. As an important t…

cs.CV202220 cited

Mugs: A Multi-Granular Self-Supervised Learning Framework

Pan Zhou, Yichen Zhou, Chenyang Si +3

In self-supervised learning, multi-granular features are heavily desired though rarely investigated, as different downstream tasks (e.g., general and fine-grained classification) o…

cs.CV2021

Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images

Wentao Chen, Chenyang Si, Wei Wang +3

Few-shot learning is a challenging task since only few instances are given for recognizing an unseen class. One way to alleviate this problem is to acquire a strong inductive bias…

cs.CV20206 cited

Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition

Chenyang Si, Xuecheng Nie, Wei Wang +3

We consider the problem of semi-supervised 3D action recognition which has been rarely explored before. Its major challenge lies in how to effectively learn motion representations…

cs.CV20191 cited

Progressive Cluster Purification for Transductive Few-shot Learning

Chenyang Si, Wentao Chen, Wei Wang +2

Few-shot learning aims to learn to generalize a classifier to novel classes with limited labeled data. Transductive inference that utilizes unlabeled test set to deal with low-data…