Papers › Learning Instance-level Spatial-Temporal Patterns for Person Re-identification

Learning Instance-level Spatial-Temporal Patterns for Person Re-identification

31 Jul 2021ICCV 2021 10arXiv:2108.00171archive 2025-07-28

Min Ren, Lingxiao He, Xingyu Liao, Wu Liu, Yunlong Wang, Tieniu Tan

Person re-identification (Re-ID) aims to match pedestrians under dis-joint cameras. Most Re-ID methods formulate it as visual representation learning and image search, and its accuracy is consequently affected greatly by the search space. Spatial-temporal information has been proven to be efficient to filter irrelevant negative samples and significantly improve Re-ID accuracy. However, existing spatial-temporal person Re-ID methods are still rough and do not exploit spatial-temporal information sufficiently. In this paper, we propose a novel Instance-level and Spatial-Temporal Disentangled Re-ID method (InSTD), to improve Re-ID accuracy. In our proposed framework, personalized information such as moving direction is explicitly considered to further narrow down the search space. Besides, the spatial-temporal transferring probability is disentangled from joint distribution to marginal distribution, so that outliers can also be well modeled. Abundant experimental analyses are presented, which demonstrates the superiority and provides more insights into our method. The proposed method achieves mAP of 90.8% on Market-1501 and 89.1% on DukeMTMC-reID, improving from the baseline 82.2% and 72.7%, respectively. Besides, in order to provide a better benchmark for person re-identification, we release a cleaned data list of DukeMTMC-reID with this paper: https://github.com/RenMin1991/cleaned-DukeMTMC-reID/

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RenMin1991/cleaned-DukeMTMC-reID officialmentioned in papermentioned on GitHub report

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Image RetrievalPerson Re-IdentificationRepresentation Learning

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Person Re-Identification DukeMTMC-reID st-ReID+InSTD mAP 89.1 #15 of 94 Archive leaderboard report
Person Re-Identification Market-1501 st-ReID+InSTD mAP 90.8 #128 of 135 Archive leaderboard report

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