activity
20212023
most citedHierarchical Feature Alignment Network for Unsupervised Video Object Segmentation

2 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2024

USDRL: Unified Skeleton-Based Dense Representation Learning with Multi-Grained Feature Decorrelation

Wanjiang Weng, Hongsong Wang, Junbo Wang +2

Contrastive learning has achieved great success in skeleton-based representation learning recently. However, the prevailing methods are predominantly negative-based, necessitating…

cs.CV202412 cited

Visual-Semantic Graph Matching Net for Zero-Shot Learning

Bowen Duan, Shiming Chen, Yufei Guo +3

Zero-shot learning (ZSL) aims to leverage additional semantic information to recognize unseen classes. To transfer knowledge from seen to unseen classes, most ZSL methods often lea…

cs.CV2024

CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network

Jie Wen, Zheng Zhang, Yong Xu +3

In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a…

cs.CV2023

Holistic Prototype Attention Network for Few-Shot VOS

Yin Tang, Tao Chen, Xiruo Jiang +3

Few-shot video object segmentation (FSVOS) aims to segment dynamic objects of unseen classes by resorting to a small set of support images that contain pixel-level object annotatio…

cs.CV2023

Learning Anchor Transformations for 3D Garment Animation

Fang Zhao, Zekun Li, Shaoli Huang +5

This paper proposes an anchor-based deformation model, namely AnchorDEF, to predict 3D garment animation from a body motion sequence. It deforms a garment mesh template by a mixtur…

cs.CV20222 cited

Hierarchical Feature Alignment Network for Unsupervised Video Object Segmentation

Gensheng Pei, Fumin Shen, Yazhou Yao +3

Optical flow is an easily conceived and precious cue for advancing unsupervised video object segmentation (UVOS). Most of the previous methods directly extract and fuse the motion…