MarKey: Marginal Utility Guided Greedy Keyframe Selection for Long Video Understanding
Long-video understanding remains challenging for multimodal large language models (MLLMs) because densely encoding long frame sequences is computationally expensive, while uniform sampling under a limited visual budget can miss sparse yet decisive evidence. Recent training-free keyframe selection methods have enabled more efficient inference and yielded promising performance gains. However, many existing methods score frames largely in isolation without explicitly considering how each candidate complements the currently selected subset, potentially resulting in redundant selections and incomplete evidence coverage. To address this limitation, we propose MarKey, a training-free framework t...
| Authors | Hongchang Shi, Jinpeng Hu, Ao Wang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 September 2026 |
| Last updated at source | 14 September 2026 |
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