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arXiv Computer Vision By Oron Nir, Eliyahu Strugo, Ariel Shamir

MINER: Modeling Inter- and Intra-Person Variance for Reidentification

Read the original on arXiv Computer Vision →

MINER is a model-agnostic framework designed to improve clothes-changing person re-identification by suppressing garment bias. It works by contrasting hard examples and adaptively balancing intra- and inter-person variance in the dataset. Experiments demonstrate that MINER achieves state-of-the-art performance on four CC-ReID benchmarks and ranks among the leaders in all three tracks of the open TVRID RGB-Depth ReID challenge.

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