Papers with Q-ViD

1 papers
Question-Instructed Visual Descriptions for Zero-Shot Video Answering (2024.findings-acl)

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Challenge: Existing models for video QA rely on complex architectures, expensive pipelines or closed models like GPTs.
Approach: They propose a single instruction-aware open vision-language model to tackle videoQA using frame descriptions.
Outcome: The proposed framework achieves higher performance than current state-of-the-art models on videoQA benchmarks.

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