1 project for "joint" with 2 filters applied:

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    JEPA

    JEPA

    PyTorch code and models for V-JEPA self-supervised learning from video

    JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture.
    Downloads: 4 This Week
    Last Update:
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