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International Institute of Information Technology
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Learning motion feasibility from raw RGB-D data can achieve near-perfect accuracy while drastically reducing computational costs compared to traditional methods.
Get 2.2x memory savings in your video VLMs without sacrificing accuracy by proactively pruning the KV-cache using optical flow and saliency, *before* computing attention.