Divide, then Ground: Adapting Frame Selection to Query Types for Long-Form Video Understanding

1. 1Identify query types for long-form video understanding
2. 2Develop frame selection methods adapted to each query type
3. 3Evaluate the computational efficiency of the proposed approach
4. 4Compare with existing query-aware frame selection methods

AI engineers and researchers working on multimodal models can benefit from this approach to improve video understanding efficiency, and product managers can apply this to develop more efficient video analysis products

💡 Adapting frame selection to query types can reduce computational overhead in long-form video understanding

💡 Efficient video understanding with adapted frame selection