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Koala: Key frame-conditioned long video-LLM
April 9, 2024, 4:46 a.m. | Reuben Tan, Ximeng Sun, Ping Hu, Jui-hsien Wang, Hanieh Deilamsalehy, Bryan A. Plummer, Bryan Russell, Kate Saenko
cs.CV updates on arXiv.org arxiv.org
Abstract: Long video question answering is a challenging task that involves recognizing short-term activities and reasoning about their fine-grained relationships. State-of-the-art video Large Language Models (vLLMs) hold promise as a viable solution due to their demonstrated emergent capabilities on new tasks. However, despite being trained on millions of short seconds-long videos, vLLMs are unable to understand minutes-long videos and accurately answer questions about them. To address this limitation, we propose a lightweight and self-supervised approach, Key …
abstract art arxiv capabilities cs.cv fine-grained however key koala language language models large language large language models llm question question answering reasoning relationships solution state tasks type video videos
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