activity
20142024
most citedCo-attention Propagation Network for Zero-Shot Video Object Segmentation

20 citations · 38 across the 10 of their papers we have counts for

collaborators

10 papers

cs.MM2024

Dual Dynamic Threshold Adjustment Strategy for Deep Metric Learning

Xiruo Jiang, Yazhou Yao, Sheng Liu +3

Loss functions and sample mining strategies are essential components in deep metric learning algorithms. However, the existing loss function or mining strategy often necessitate th…

cs.CV20233 cited

MSFlow: Multi-Scale Flow-based Framework for Unsupervised Anomaly Detection

Yixuan Zhou, Xing Xu, Jingkuan Song +2

Unsupervised anomaly detection (UAD) attracts a lot of research interest and drives widespread applications, where only anomaly-free samples are available for training. Some UAD ap…

cs.CV202320 cited

Co-attention Propagation Network for Zero-Shot Video Object Segmentation

Gensheng Pei, Yazhou Yao, Fumin Shen +3

Zero-shot video object segmentation (ZS-VOS) aims to segment foreground objects in a video sequence without prior knowledge of these objects. However, existing ZS-VOS methods often…

cs.CV20232 cited

Attention Map Guided Transformer Pruning for Edge Device

Junzhu Mao, Yazhou Yao, Zeren Sun +3

Due to its significant capability of modeling long-range dependencies, vision transformer (ViT) has achieved promising success in both holistic and occluded person re-identificatio…

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…

cs.CV20171 cited

Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation

Xinyu Wang, Hanxi Li, Yi Li +2

Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due t…