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Beyond Flat Labels: Level-Restricted Contrastive Learning for Hierarchical Fine-Grained Vision Classification

This work proposes to restrict contrastive comparisons to categories within the same taxonomic level, and adopts a group-balanced design, ensuring each taxonomic level receives adequate optimization and improves both hierarchical consistency and classification accuracy from coarse to fine granularity.

Zhi-Yuan Tao, S. Sastry, Matthew J. Thompson et al. · 0 citations

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