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SMILE: Infusing Spatial and Motion Semantics in Masked Video Learning

Published in CVPR, 2025

This paper proposes SMILE, a self-supervised video learning method that improves semantic and motion representation by incorporating CLIP-guided spatial semantics and synthetic motion patterns, achieving state-of-the-art results across 7 datasets.

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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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