Papers › Intra-Inter Camera Similarity for Unsupervised Person Re-Identification

Intra-Inter Camera Similarity for Unsupervised Person Re-Identification

22 Mar 2021CVPR 2021 1arXiv:2103.11658archive 2025-07-28

Shiyu Xuan, Shiliang Zhang

Most of unsupervised person Re-Identification (Re-ID) works produce pseudo-labels by measuring the feature similarity without considering the distribution discrepancy among cameras, leading to degraded accuracy in label computation across cameras. This paper targets to address this challenge by studying a novel intra-inter camera similarity for pseudo-label generation. We decompose the sample similarity computation into two stage, i.e., the intra-camera and inter-camera computations, respectively. The intra-camera computation directly leverages the CNN features for similarity computation within each camera. Pseudo-labels generated on different cameras train the re-id model in a multi-branch network. The second stage considers the classification scores of each sample on different cameras as a new feature vector. This new feature effectively alleviates the distribution discrepancy among cameras and generates more reliable pseudo-labels. We hence train our re-id model in two stages with intra-camera and inter-camera pseudo-labels, respectively. This simple intra-inter camera similarity produces surprisingly good performance on multiple datasets, e.g., achieves rank-1 accuracy of 89.5% on the Market1501 dataset, outperforming the recent unsupervised works by 9+%, and is comparable with the latest transfer learning works that leverage extra annotations.

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distance_cross_cam SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository ran · our draft was wrong no licence file found · pointer only · 3b7f62d9b5bdf726 · report
extract_features_cross_cam SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository ran · fixture could not drive it no licence file found · pointer only · 41593cadd09732cd · report
jaccard_sim_cross_cam SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository ran · our draft was wrong no licence file found · pointer only · 03281e3d606fc1d7 · report
re_ranking SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · 847157d20d50a955 · report
to_numpy SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository ran · honoured contract no licence file found · pointer only · b476623700945834 · report
cluster_cross_cam SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository unverified no licence file found · pointer only · 8a5f3e3b87722723 · report
extract_cnn_feature SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository unverified no licence file found · pointer only · a76ce960a58c48d8 · report
get_inter_cam_cluster_result SY-Xuan/IICS/reid/cluster_utils/cluster.py official repository unverified no licence file found · pointer only · 4727d5aadf8d272d · report

Tasks

Person Re-IdentificationPseudo LabelTransfer LearningUnsupervised Person Re-Identification

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Person Re-Identification SYSU-30k IICS (generalization) Rank-1 36.0 #1 of 10 Archive leaderboard report
Unsupervised Person Re-Identification DukeMTMCreID IICS Rank-1 80.0 #1 of 2 Archive leaderboard report
Unsupervised Person Re-Identification Market-1501 IICS MAP 72.9 #16 of 23 Archive leaderboard report
Unsupervised Person Re-Identification Market-1501 IICS Rank-1 89.5 #16 of 23 Archive leaderboard report
Unsupervised Person Re-Identification Market-1501 IICS Rank-10 97.0 #16 of 23 Archive leaderboard report
Unsupervised Person Re-Identification Market-1501 IICS Rank-5 95.2 #16 of 23 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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