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    JEPA

    JEPA

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

    ...The repository provides training recipes, data pipelines, and evaluation utilities for image JEPA variants and often includes ablations that illuminate which masking and architectural choices matter. Because the objective is non-autoregressive and operates in embedding space, JEPA tends to be compute-efficient and stable at scale. The approach has become a strong alternative to contrastive or pixel-reconstruction methods for representation learning.
    Downloads: 0 This Week
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