MOTR: End-to-End Multiple-Object Tracking with Transformer.

European Conference on Computer Vision(2022)

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摘要
Temporal modeling of objects is a key challenge in multiple-object tracking (MOT). Existing methods track by associating detections through motion-based and appearance-based similarity heuristics. The post-processing nature of association prevents end-to-end exploitation of temporal variations in video sequence.
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关键词
Multiple-object tracking,Transformer,End-to-End
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