activity
20182022
most citedA Two-Stage Attentive Network for Single Image Super-Resolution

85 citations · 192 across the 13 of their papers we have counts for

collaborators
Showing cs.CVShow all

16 papers · 1 filter

cs.CV20221 cited

Explore Contextual Information for 3D Scene Graph Generation

Yuanyuan Liu, Chengjiang Long, Zhaoxuan Zhang +4

3D scene graph generation (SGG) has been of high interest in computer vision. Although the accuracy of 3D SGG on coarse classification and single relation label has been gradually…

cs.CV2022

Wider and Higher: Intensive Integration and Global Foreground Perception for Image Matting

Yu Qiao, Ziqi Wei, Yuhao Liu +4

This paper reviews recent deep-learning-based matting research and conceives our wider and higher motivation for image matting. Many approaches achieve alpha mattes with complex en…

cs.CV202222 cited

Large-Field Contextual Feature Learning for Glass Detection

Haiyang Mei, Xin Yang, Letian Yu +3

Glass is very common in our daily life. Existing computer vision systems neglect it and thus may have severe consequences, e.g., a robot may crash into a glass wall. However, sensi…

cs.CV2022

Bi-directional Object-context Prioritization Learning for Saliency Ranking

Xin Tian, Ke Xu, Xin Yang +3

The saliency ranking task is recently proposed to study the visual behavior that humans would typically shift their attention over different objects of a scene based on their degre…

cs.CV20215 cited

Object Tracking by Jointly Exploiting Frame and Event Domain

Jiqing Zhang, Xin Yang, Yingkai Fu +3

Inspired by the complementarity between conventional frame-based and bio-inspired event-based cameras, we propose a multi-modal based approach to fuse visual cues from the frame- a…

cs.CV2021

Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking

Jiqing Zhang, Kai Zhao, Bo Dong +4

Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking. This paper focuses on effective…