This repo experiments with cross-data evaluation from pre-existing datasets such as Market1501 and CUKH-03 on our collected dataset.
These experiments utilize the TorchReid Library created by Kaiyang Zhou https://kaiyangzhou.github.io/deep-person-reid/ as a means to test Cross-Entropy and Triplet Loss Function's effects on mAP, and rank accuracies on collected datasets.
Market 1501 https://deepai.org/dataset/market-1501
Market-1501 dataset annotates 27 attributes, containing 751 identities for training and 750 for testing, that are annotated in the identity level. Thus, the file contains 27 x 751 attributes for training and 27 x 750 for test.
These images are used for cross-data evaluation on our dataset containing two disjoint cameras in various variable environment settings (lighting, view, background).
But also, performed poorly in some examples,
| Softmax+CLE (Crop, Flip) | Softmax+CLE(Crop, Flip, CJitter, Patch) | TripletLoss (Crop, Flip) | |
|---|---|---|---|
| mAP | 45.6% | 92.9% | 95.4% |
| Rank@1 | 10.1% | 97.1% | 95.6% |
| Rank@5 | 25.3% | 100.0% | 98.5% |
| Rank@10 | 53.2% | 100.0% | 98.5% |
| Rank@20 | 63.3% | 100.0% | 98.5% |
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[2] Li, W., Zhao, R., Xiao, T., & Wang, X. (2014). DeepReID: Deep Filter Pairing Neural Network for Person Re-identification. 2014 IEEE Conference on Computer Vision and Pattern Recognition. doi:10.1109/cvpr.2014.27
[3] Wang, G., Lai, J., Huang, P., & Xie, X. (2018). Spatial-Temporal Person Re-identification. Retrieved December 15, 2020, from https://arxiv.org/pdf/1812.03282v1.pdf
[4] Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., & Tian, Q. (2015). Scalable Person Re-Identification: A Benchmark. Retrieved December 16, 2020, from https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Zheng_Scalable_Person_Re-Identification_ICCV_2015_paper.pdf
[5] Zhong, Z., Zheng, L., Zheng, Z., Li, S., & Yang, Y. (2018). Camera Style Adaptation for Person Re-identification. Retrieved December 15, 2020, from https://arxiv.org/pdf/1711.10295.pdf
[6] Li, W., Zhao, R., Xiao, T., & Wang, X. (2014). DeepReID: Deep Filter Pairing Neural Network for Person Re-identification. 2014 IEEE Conference on Computer Vision and Pattern Recognition. doi:10.1109/cvpr.2014.27
[7] Hirzer, M., Beleznai, C., Roth, P., & Bischof, H. (2011). Person Re-identification by Descriptive and Discriminative Classification. SCIA.