7 papers
STEP: Surgical Point Tracking from Sparse Endpoints and Pseudo-trajectories
Bing Fan, Anwesa Choudhuri, Zhongpai Gao +5
Surgical point tracking requires persistent correspondence through tissue deformation and occlusion, yet dense trajectory annotations are costly to obtain. We present STEP, a two-s…
RGBD20K: A Large-Scale Benchmark for RGB-D Semantic Segmentation
Shaohua Dong, Zexuan Meng, Haiyan Sun +6
In this paper, we propose RGBD20K, a novel dataset for facilitating the development of more robust and general RGB-D semantic segmentation by encompassing abundant categories and h…
Towards Visual Query Segmentation in the Wild
Bing Fan, Minghao Li, Hanzhi Zhang +6
In this paper, we introduce visual query segmentation (VQS), a new paradigm of visual query localization (VQL) that aims to segment all pixel-level occurrences of an object of inte…
Towards Long-Form Spatio-Temporal Video Grounding
Xin Gu, Bing Fan, Jiali Yao +5
In real scenarios, videos can span several minutes or even hours. However, existing research on spatio-temporal video grounding (STVG), given a textual query, mainly focuses on loc…
Robust Ego-Exo Correspondence with Long-Term Memory
Yijun Hu, Bing Fan, Xin Gu +4
Establishing object-level correspondence between egocentric and exocentric views is essential for intelligent assistants to deliver precise and intuitive visual guidance. However,…
OmniSTVG: Toward Spatio-Temporal Omni-Object Video Grounding
Jiali Yao, Xinran Deng, Xin Gu +6
In this paper, we propose spatio-temporal omni-object video grounding, dubbed OmniSTVG, a new STVG task that aims at localizing spatially and temporally all targets mentioned in th…
PRVQL: Progressive Knowledge-guided Refinement for Robust Egocentric Visual Query Localization
Bing Fan, Yunhe Feng, Yapeng Tian +4
Egocentric visual query localization (EgoVQL) focuses on localizing the target of interest in space and time from first-person videos, given a visual query. Despite recent progress…