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Found 3 papers, 2 papers with code
FILS: Self-Supervised Video Feature Prediction In Semantic Language Space
Our goal is to achieve a more semantic video representation by leveraging the text related to the video content during the pretraining in a fully self-supervised manner.
MOFO: MOtion FOcused Self-Supervision for Video Understanding
Despite the importance of motion in supervised learning techniques for action recognition, SSL methods often do not explicitly consider motion information in videos.
Heterogeneous Graph Learning for Acoustic Event Classification
Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities.
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