Papers › Harmonious Attention Network for Person Re-Identification
Harmonious Attention Network for Person Re-Identification
Wei Li, Xiatian Zhu, Shaogang Gong
Existing person re-identification (re-id) methods either assume the availability of well-aligned person bounding box images as model input or rely on constrained attention selection mechanisms to calibrate misaligned images. They are therefore sub-optimal for re-id matching in arbitrarily aligned person images potentially with large human pose variations and unconstrained auto-detection errors. In this work, we show the advantages of jointly learning attention selection and feature representation in a Convolutional Neural Network (CNN) by maximising the complementary information of different levels of visual attention subject to re-id discriminative learning constraints. Specifically, we formulate a novel Harmonious Attention CNN (HA-CNN) model for joint learning of soft pixel attention and hard regional attention along with simultaneous optimisation of feature representations, dedicated to optimise person re-id in uncontrolled (misaligned) images. Extensive comparative evaluations validate the superiority of this new HA-CNN model for person re-id over a wide variety of state-of-the-art methods on three large-scale benchmarks including CUHK03, Market-1501, and DukeMTMC-ReID.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Person Re-Identification | CUHK03 | HA-CNN | MAP | 38.6 | #15 of 19 | Archive leaderboard | report |
| Person Re-Identification | CUHK03 | HA-CNN | Rank-1 | 41.7 | #15 of 19 | Archive leaderboard | report |
| Person Re-Identification | CUHK03 detected | HA-CNN (CVPR'18) | MAP | 38.6 | #13 of 19 | Archive leaderboard | report |
| Person Re-Identification | CUHK03 detected | HA-CNN (CVPR'18) | Rank-1 | 41.7 | #13 of 19 | Archive leaderboard | report |
| Person Re-Identification | CUHK03 labeled | HA-CNN (CVPR'18) | MAP | 41.0 | #16 of 21 | Archive leaderboard | report |
| Person Re-Identification | CUHK03 labeled | HA-CNN (CVPR'18) | Rank-1 | 44.4 | #16 of 21 | 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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