Papers › Camera Style Adaptation for Person Re-identification
Camera Style Adaptation for Person Re-identification
Zhun Zhong, Liang Zheng, Zhedong Zheng, Shaozi Li, Yi Yang
Being a cross-camera retrieval task, person re-identification suffers from image style variations caused by different cameras. The art implicitly addresses this problem by learning a camera-invariant descriptor subspace. In this paper, we explicitly consider this challenge by introducing camera style (CamStyle) adaptation. CamStyle can serve as a data augmentation approach that smooths the camera style disparities. Specifically, with CycleGAN, labeled training images can be style-transferred to each camera, and, along with the original training samples, form the augmented training set. This method, while increasing data diversity against over-fitting, also incurs a considerable level of noise. In the effort to alleviate the impact of noise, the label smooth regularization (LSR) is adopted. The vanilla version of our method (without LSR) performs reasonably well on few-camera systems in which over-fitting often occurs. With LSR, we demonstrate consistent improvement in all systems regardless of the extent of over-fitting. We also report competitive accuracy compared with the state of the art.
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Code
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Code Syntology ran Syntology
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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 | DukeMTMC-reID | IDE* + CamStyle + Random Erasing | Rank-1 | 78.32 | #75 of 94 | Archive leaderboard | report |
| Person Re-Identification | DukeMTMC-reID | IDE* + CamStyle + Random Erasing | mAP | 57.61 | #75 of 94 | Archive leaderboard | report |
| Person Re-Identification | DukeMTMC-reID | IDE* | Rank-1 | 72.31 | #80 of 94 | Archive leaderboard | report |
| Person Re-Identification | DukeMTMC-reID | IDE* | mAP | 51.83 | #80 of 94 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | IDE* + CamStyle + Random Erasing | Rank-1 | 89.49 | #95 of 135 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | IDE* + CamStyle + Random Erasing | mAP | 71.55 | #95 of 135 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | IDE* | Rank-1 | 85.66 | #103 of 135 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | IDE* | mAP | 65.87 | #103 of 135 | 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.
Methods
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