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Found 2 papers, 1 papers with code
TransCenter: Transformers with Dense Representations for Multiple-Object Tracking
Methodologically, we propose the use of image-related dense detection queries and efficient sparse tracking queries produced by our carefully designed query learning networks (QLN).
Ranked #13 on
Multi-Object Tracking
on MOT20
(using extra training data)
CANU-ReID: A Conditional Adversarial Network for Unsupervised person Re-IDentification
Unsupervised person re-ID is the task of identifying people on a target data set for which the ID labels are unavailable during training.
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