TOMM2018_Unsupervised Person Re-identification: Clustering and Fine-tuning
Unsupervised Person Re-identification: Clustering and Fine-tuning 思想很清晰： a) 用其他的標註數據集先訓練一個pre-trained model； b) 用這個model提取training的特徵 c) 把提取的feature做一個K均值分類，然後算一箇中心特徵 d) 每類距離
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相關文章
- 1. Unsupervised Person Re-identification: Clustering and Fine-tuning
- 2. Unsupervised Person Re-identification: Clustering and Fine-tuning
- 3. Unsupervised Person Re-identification: Clustering and Fine-tuning閱讀筆記
- 4. SYSU-MM01的多模態Re-ID數據集 異構Heterogeneous person reidentification
- 5. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 6. 【Person Re-ID】Person Re-identification: Past, Present and Future
- 7. BIRCH：Balanced Iterative Reducing and Clustering Using Hierarchis
- 8. [CS131] Lecture 10 Semantic Segmentation and Clustering
- 9. Kernel Clustering: Density Biases and Solutions
- 10. 【論文2】AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification