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

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Hi authors, I have a question about this line https://github.com/facebookresearch/jepa/blob/main/evals/video_classification_frozen/utils.py#L74 where we're using the frame-indices to generate the positional encodings. I'm a little confused looking at the clip-indices being over-written...

Hello, I currently want to use my own dataset using the V-JEPA method to reconstruct images similarly to the way shown in Figure 6b of your paper. Do you have...

Hello Everyone, I've been working with the V-JEPA model for a self-supervised learning project using a custom video dataset. Initially, the training loss decreases as expected, but starts to increase...

Hi, According to the paper, autoaugment is only used for the images classification (with the cross attention head), but in the [code](https://github.com/facebookresearch/jepa/blob/main/evals/video_classification_frozen/eval.py#L467) AA is on for the videos as well,...

Hi, Thank you for this amazing project. I have been exploring the feature maps produced by the pre-trained V-JEPA, using PCA component visualization. ![image](https://github.com/facebookresearch/jepa/assets/10291299/02b1ec82-dbb7-4e28-88c2-05cb9990c929) However, the feature maps look very...