ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.
arXiv preprint arXiv:2401.16702 , year=
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R-FUML models network outputs as fuzzy memberships, applies entropy-based robust multi-view fusion, and uses memory-effect isolation plus penalties to mitigate view conflicts, outperforming 15 baselines on eight datasets.
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ROGLE: Robust Global-Local Alignment with Automated Region Supervision for Text-Based Person Search
ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.
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Robust Fuzzy Multi-view Learning under View Conflict
R-FUML models network outputs as fuzzy memberships, applies entropy-based robust multi-view fusion, and uses memory-effect isolation plus penalties to mitigate view conflicts, outperforming 15 baselines on eight datasets.
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