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Found 2 papers, 2 papers with code
Contrastive Learning for OOD in Object detection
Contrastive learning is commonly applied to self-supervised learning, and has been shown to outperform traditional approaches such as the triplet loss and N-pair loss.
Contrastive Learning for Object Detection
Contrastive learning is commonly used as a method of self-supervised learning with the "anchor" and "positive" being two random augmentations of a given input image, and the "negative" is the set of all other images.
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