0000000000746465

AUTHOR

Sander Riisøen Jyhne

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Contrastive Transformer: Contrastive Learning Scheme with Transformer innate Patches

2023

This paper presents Contrastive Transformer, a contrastive learning scheme using the Transformer innate patches. Contrastive Transformer enables existing contrastive learning techniques, often used for image classification, to benefit dense downstream prediction tasks such as semantic segmentation. The scheme performs supervised patch-level contrastive learning, selecting the patches based on the ground truth mask, subsequently used for hard-negative and hard-positive sampling. The scheme applies to all vision-transformer architectures, is easy to implement, and introduces minimal additional memory footprint. Additionally, the scheme removes the need for huge batch sizes, as each patch is t…

FOS: Computer and information sciencesArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition
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