Meet MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features

Recently, techniques focusing on learning content features—specifically, features holding the information that lets us identify and discriminate objects—have dominated self-supervised learning in vision. Most techniques concentrate on identifying broad characteristics that perform well in tasks like item categorization or activity detection in films. Learning localized features that excel at regional tasks like segmentation and detection […]

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