15 citations · 19 across the 9 of their papers we have counts for
10 papers · 1 filter
Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation
Changwei Xu, Jianfei Yang, Haoran Tang +3
Unsupervised Domain Adaptation (UDA), a branch of transfer learning where labels for target samples are unavailable, has been widely researched and developed in recent years with t…
Suppressing Mislabeled Data via Grouping and Self-Attention
Xiaojiang Peng, Kai Wang, Zhaoyang Zeng +3
Deep networks achieve excellent results on large-scale clean data but degrade significantly when learning from noisy labels. To suppressing the impact of mislabeled data, this pape…
Effective Action Recognition with Embedded Key Point Shifts
Haozhi Cao, Yuecong Xu, Jianfei Yang +3
Temporal feature extraction is an essential technique in video-based action recognition. Key points have been utilized in skeleton-based action recognition methods but they require…
PNL: Efficient Long-Range Dependencies Extraction with Pyramid Non-Local Module for Action Recognition
Yuecong Xu, Haozhi Cao, Jianfei Yang +3
Long-range spatiotemporal dependencies capturing plays an essential role in improving video features for action recognition. The non-local block inspired by the non-local means is…
Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition
Yuecong Xu, Jianfei Yang, Kezhi Mao +2
Temporal feature extraction is an important issue in video-based action recognition. Optical flow is a popular method to extract temporal feature, which produces excellent performa…
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
Kai Wang, Xiaojiang Peng, Jianfei Yang +2
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, an…