5 papers
CVA: Context-aware Video-text Alignment for Video Temporal Grounding
Sungho Moon, Seunghun Lee, Jiwan Seo +1
We propose Context-aware Video-text Alignment (CVA), a novel framework to address a significant challenge in video temporal grounding: achieving temporally sensitive video-text ali…
Bridging Geometric and Semantic Foundation Models for Generalized Monocular Depth Estimation
Sanggyun Ma, Wonjoon Choi, Jihun Park +4
We present Bridging Geometric and Semantic (BriGeS), an effective method that fuses geometric and semantic information within foundation models to enhance Monocular Depth Estimatio…
Temporal Grounding as a Learning Signal for Referring Video Object Segmentation
Seunghun Lee, Jiwan Seo, Jeonghoon Kim +9
Referring Video Object Segmentation (RVOS) aims to segment and track objects in videos based on natural language expressions, requiring precise alignment between visual content and…
Latest Object Memory Management for Temporally Consistent Video Instance Segmentation
Seunghun Lee, Jiwan Seo, Minwoo Choi +6
In this paper, we present Latest Object Memory Management (LOMM) for temporally consistent video instance segmentation that significantly improves long-term instance tracking. At t…
CAVIS: Context-Aware Video Instance Segmentation
Seunghun Lee, Jiwan Seo, Kiljoon Han +2
In this paper, we introduce the Context-Aware Video Instance Segmentation (CAVIS), a novel framework designed to enhance instance association by integrating contextual information…