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RGNet: A Unified Clip Retrieval and Grounding Network for Long Videos
March 25, 2024, 4:45 a.m. | Tanveer Hannan, Md Mohaiminul Islam, Thomas Seidl, Gedas Bertasius
cs.CV updates on arXiv.org arxiv.org
Abstract: Locating specific moments within long videos (20-120 minutes) presents a significant challenge, akin to finding a needle in a haystack. Adapting existing short video (5-30 seconds) grounding methods to this problem yields poor performance. Since most real life videos, such as those on YouTube and AR/VR, are lengthy, addressing this issue is crucial. Existing methods typically operate in two stages: clip retrieval and grounding. However, this disjoint process limits the retrieval module's fine-grained event understanding, …
abstract arxiv challenge clip cs.cv haystack life moments network performance retrieval type video videos youtube
More from arxiv.org / cs.CV updates on arXiv.org
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
2 days, 2 hours ago |
arxiv.org
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