SOURCE-LINKED INTELLIGENCE

Cross-Species Animal Re-Identification with Semantic Consistency Learning

arXiv · AI, language, vision and robotics · article · Sep 9, 2026 · UTC

Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Unlike person ReID, where different domains share similar body structures, animal species often exhibit drastically different anatomical structures and visual patterns, making it difficult to establish shared visual correspondences. As a result, representations learned across species tend to form fragmented embedding spaces, which severely limits cross-species generalization. To address this challenge, we propose Semantic Consistency Learning (SCL

Read original source ↗ Open in workspace

recordType

paper

region

Global