A multi-view semantic reformulation and feature compensation method using LLMs and VLMs improves text-to-image person retrieval accuracy without training and reaches SOTA on three datasets.
Modality- transition representation learning for visible-infrared person re-identification
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Towards Robust Text-to-Image Person Retrieval: Multi-View Reformulation for Semantic Compensation
A multi-view semantic reformulation and feature compensation method using LLMs and VLMs improves text-to-image person retrieval accuracy without training and reaches SOTA on three datasets.