AI RESEARCH
Scale-Aware Vision-Language Adaptation for Extreme Far-Distance Video Person Re-identification
arXiv CS.CV
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ArXi:2604.04183v1 Announce Type: new Extreme far-distance video person re-identification (ReID) is particularly challenging due to scale compression, resolution degradation, motion blur, and aerial-ground viewpoint mismatch. As camera altitude and subject distance increase, models trained on close-range imagery degrade significantly. In this work, we investigate how large-scale vision-language models can be adapted to operate reliably under these conditions. Starting from a CLIP-based baseline, we upgrade the visual backbone from ViT-B/16 to ViT-L/14 and.