3 citations · 3 across the 6 of their papers we have counts for
8 papers
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…
ReCoVR: Closing the Loop in Interactive Composed Video Retrieval
Bingqing Zhang, Yi Zhang, Zhuo Cao +4
Composed video retrieval (CoVR) searches for target videos using a reference video and a modification text, but existing methods are restricted to a single interaction round and ca…
Robust Test-time Video-Text Retrieval: Benchmarking and Adapting for Query Shifts
Bingqing Zhang, Zhuo Cao, Heming Du +4
Modern video-text retrieval (VTR) models excel on in-distribution benchmarks but are highly vulnerable to real-world query shifts, where the distribution of query data deviates fro…
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…
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…
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…
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.…
Object Detection Difficulty: Suppressing Over-aggregation for Faster and Better Video Object Detection
Bingqing Zhang, Sen Wang, Yifan Liu +3
Current video object detection (VOD) models often encounter issues with over-aggregation due to redundant aggregation strategies, which perform feature aggregation on every frame.…