5 papers
Video Understanding: From Geometry and Semantics to Unified Models
Zhaochong An, Zirui Li, Mingqiao Ye +9
Video understanding aims to enable models to perceive, reason about, and interact with the dynamic visual world. In contrast to image understanding, video understanding inherently…
EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark
Deheng Zhang, Yuqian Fu, Runyi Yang +9
Most existing benchmarks for understanding egocentric vision focus primarily on daytime scenarios, overlooking the low-light conditions that are inevitable in real-world applicatio…
ObjectRelator: Enabling Cross-View Object Relation Understanding Across Ego-Centric and Exo-Centric Perspectives
Yuqian Fu, Runze Wang, Bin Ren +6
Bridging the gap between ego-centric and exo-centric views has been a long-standing question in computer vision. In this paper, we focus on the emerging Ego-Exo object corresponden…
RGB-D Indiscernible Object Counting in Underwater Scenes
Guolei Sun, Xiaogang Cheng, Zhaochong An +5
Recently, indiscernible/camouflaged scene understanding has attracted lots of research attention in the vision community. We further advance the frontier of this field by systemati…
XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
Yuedong Tan, Zongwei Wu, Yuqian Fu +7
Multimodal sensing has proven valuable for visual tracking, as different sensor types offer unique strengths in handling one specific challenging scene where object appearance vari…