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Hierarchical Memory for Long Video QA

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arxiv 2407.00603 v2 pith:OJYTNIZ7 submitted 2024-06-30 cs.CV

Hierarchical Memory for Long Video QA

Yiqin Wang , Haoji Zhang , Yansong Tang , Yong Liu , Jiashi Feng , Jifeng Dai , Xiaojie Jin This is my paper
classification cs.CV
keywords longmemoryvideochallengeflash-vstreamhierarchicalprocessingquestion-answering
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper describes our champion solution to the LOVEU Challenge @ CVPR'24, Track 1 (Long Video VQA). Processing long sequences of visual tokens is computationally expensive and memory-intensive, making long video question-answering a challenging task. The key is to compress visual tokens effectively, reducing memory footprint and decoding latency, while preserving the essential information for accurate question-answering. We adopt a hierarchical memory mechanism named STAR Memory, proposed in Flash-VStream, that is capable of processing long videos with limited GPU memory (VRAM). We further utilize the video and audio data of MovieChat-1K training set to fine-tune the pretrained weight released by Flash-VStream, achieving 1st place in the challenge. Code is available at project homepage https://invinciblewyq.github.io/vstream-page .

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