UATTA adapts pre-trained text-image models at test time without labels by using disagreement in bidirectional retrieval rankings to estimate and mitigate uncertainty for improved person search.
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A teacher-student model with co-saliency network and growing-probability occlusion simulator outperforms prior methods on four occluded person re-identification benchmarks.
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Pretrain-then-Adapt: Uncertainty-Aware Test-Time Adaptation for Text-based Person Search
UATTA adapts pre-trained text-image models at test time without labels by using disagreement in bidirectional retrieval rankings to estimate and mitigate uncertainty for improved person search.
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A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification
A teacher-student model with co-saliency network and growing-probability occlusion simulator outperforms prior methods on four occluded person re-identification benchmarks.