2024
DOI: 10.21203/rs.3.rs-4662935/v1
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Patch-Wise Self-Supervised Visual Representation Learning: A Fine-Grained Approach

Ali Javidani,
Mohammad Amin Sadeghi,
Babak Nadjar Araabi

Abstract: Self-supervised visual representation learning traditionally focuses on image-level instance discrimination. Our study introduces an innovative, fine-grained dimension by integrating patch-level discrimination into these methodologies. This integration allows for the simultaneous analysis of local and global visual features, thereby enriching the quality of the learned representations. Initially, the original images undergo spatial augmentation. Subsequently, we employ a distinctive photometric patch-level aug… Show more

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