A Lightweight Moment Retrieval System with Global Re-Ranking and Robust Adaptive Bidirectional Temporal Search
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arXiv
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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910910576066560 |
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| author | Nguyen-Nhu, Tinh-Anh Tran, Huu-Loc Le, Nguyen-Khang Nguyen, Minh-Nhat Nguyen, Tien-Huy Nguyen-Huu, Hoang-Long Phan-Nguyen, Huu-Phong Pham, Huy-Thach Nguyen, Quan Le, Hoang M. Dinh, Quang-Vinh |
| author_facet | Nguyen-Nhu, Tinh-Anh Tran, Huu-Loc Le, Nguyen-Khang Nguyen, Minh-Nhat Nguyen, Tien-Huy Nguyen-Huu, Hoang-Long Phan-Nguyen, Huu-Phong Pham, Huy-Thach Nguyen, Quan Le, Hoang M. Dinh, Quang-Vinh |
| contents | The exponential growth of digital video content has posed critical challenges in moment-level video retrieval, where existing methodologies struggle to efficiently localize specific segments within an expansive video corpus. Current retrieval systems are constrained by computational inefficiencies, temporal context limitations, and the intrinsic complexity of navigating video content. In this paper, we address these limitations through a novel Interactive Video Corpus Moment Retrieval framework that integrates a SuperGlobal Reranking mechanism and Adaptive Bidirectional Temporal Search (ABTS), strategically optimizing query similarity, temporal stability, and computational resources. By preprocessing a large corpus of videos using a keyframe extraction model and deduplication technique through image hashing, our approach provides a scalable solution that significantly reduces storage requirements while maintaining high localization precision across diverse video repositories. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_09298 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Lightweight Moment Retrieval System with Global Re-Ranking and Robust Adaptive Bidirectional Temporal Search Nguyen-Nhu, Tinh-Anh Tran, Huu-Loc Le, Nguyen-Khang Nguyen, Minh-Nhat Nguyen, Tien-Huy Nguyen-Huu, Hoang-Long Phan-Nguyen, Huu-Phong Pham, Huy-Thach Nguyen, Quan Le, Hoang M. Dinh, Quang-Vinh Computer Vision and Pattern Recognition The exponential growth of digital video content has posed critical challenges in moment-level video retrieval, where existing methodologies struggle to efficiently localize specific segments within an expansive video corpus. Current retrieval systems are constrained by computational inefficiencies, temporal context limitations, and the intrinsic complexity of navigating video content. In this paper, we address these limitations through a novel Interactive Video Corpus Moment Retrieval framework that integrates a SuperGlobal Reranking mechanism and Adaptive Bidirectional Temporal Search (ABTS), strategically optimizing query similarity, temporal stability, and computational resources. By preprocessing a large corpus of videos using a keyframe extraction model and deduplication technique through image hashing, our approach provides a scalable solution that significantly reduces storage requirements while maintaining high localization precision across diverse video repositories. |
| title | A Lightweight Moment Retrieval System with Global Re-Ranking and Robust Adaptive Bidirectional Temporal Search |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2504.09298 |