SwAV Loss Deep Dive
Автор: Lightning AI
Загружено: 2020-11-19
Просмотров: 3896
In this video, we dive into the loss function used in "SWaV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments".
SwAV is the latest paper from FAIR and Inria to post state of the art results in self-supervised learning. The paper combines ideas from contrastive learning and clustering based approaches to train image representations. The swapped prediction problem loss, used in SwAV, enforces consistency in cluster assignment of representations between different views of the same image.
Check out our previous video featuring walkthrough of SwAV paper with author Mathilde Caron: • Self-Supervised Learning of Image Features...
And step-by-step PyTorch Lightning implementation of SwAV: • SwAV PyTorch Lightning Implementation
You can find our implementation in Lightning Bolts, a deep learning research toolkit with SOTA models: https://pytorch-lightning-bolts.readt...
Paper: https://arxiv.org/abs/2006.09882
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Lightning Website: https://lightning.ai/
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GitHub: https://github.com/PyTorchLightning/p...
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