Multi-Level Feature Learning for Person Re-Identification
Master's thesis on deep discriminative feature learning for person re-identification.
Contributions
- Proposed a multi-level network for extracting discriminative person ReID features.
- Applied batch-hard triplet loss at multiple network levels for stronger metric learning.
- Fused features from different levels for the final classification task.
