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cs.CV2026

DSE-VTG: Dual-Side Enhancement for Training-Free Video Temporal Grounding

Zhuo Cao, Bingqing Zhang, Sen Wang +1

Text-guided Video Temporal Grounding (VTG) aims to localize the relevant segments in an untrimmed video based on text queries, yet collecting dense temporal annotations and trainin…

cs.CV2025

When One Moment Isn't Enough: Multi-Moment Retrieval with Cross-Moment Interactions

Zhuo Cao, Heming Du, Bingqing Zhang +3

Existing Moment retrieval (MR) methods focus on Single-Moment Retrieval (SMR). However, one query can correspond to multiple relevant moments in real-world applications. This makes…

cs.CV2025

Quantifying and Narrowing the Unknown: Interactive Text-to-Video Retrieval via Uncertainty Minimization

Bingqing Zhang, Zhuo Cao, Heming Du +4

Despite recent advances, Text-to-video retrieval (TVR) is still hindered by multiple inherent uncertainties, such as ambiguous textual queries, indistinct text-video mappings, and…

cs.CV2024

FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding

Zhuo Cao, Bingqing Zhang, Heming Du +3

Text-guided Video Temporal Grounding (VTG) aims to localize relevant segments in untrimmed videos based on textual descriptions, encompassing two subtasks: Moment Retrieval (MR) an…

cs.CV2024

TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm

Bingqing Zhang, Zhuo Cao, Heming Du +4

Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained, fine-grained, or combined (coarse-to-fine) manners.…