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PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition
We develop techniques for refining representations for fine-grained classification and segmentation tasks in a self-supervised manner. -
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future C...
A self-supervised spatiotemporal representation learning approach for videos, combining temporal coherence and future clip order ranking. -
Self-supervised and semi-supervised learning for GANs
Self-supervised and semi-supervised learning for GANs -
SSL-MAE dataset for TransUNet
Self-supervised learning dataset for TransUNet pretraining
