Adaptive Greedy Frame Selection for Long Video Understanding

1. 1Identify key frames in a video using a question-adaptive greedy selection method
2. 2Balance frame relevance to the question and coverage of temporally distant evidence
3. 3Optimize the number of input frames to reduce computational costs and improve inference efficiency
4. 4Evaluate the performance of the proposed method on long video question answering tasks

Computer vision engineers and researchers working on video question answering tasks can benefit from this method to optimize frame selection and improve model performance. This can be particularly useful in applications where long videos need to be analyzed efficiently

💡 Balancing relevance and coverage is crucial for effective frame selection in long video question answering

💡 Adaptive greedy frame selection for efficient long video understanding