2019 CVPR之ReID：Joint Discriminative and Generative Learning for Person Re-identification
Joint Discriminative and Generative Learning for Person Re-identification 當前的問題及概述： 目前，ReID任務通過GAN網絡訓練越來越熱門，然而，現有方法中的G途徑與D再識別學習階段相對獨立。因此，reid模型通常直接對生成的數據進行訓練。 本文提出了一個聯合學習框架，將ReID任務和端到端的圖像生成結合起來。提出的模型包
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相關文章
- 1. Joint Discriminative and Generative Learning for Person Re-identification
- 2. [CVPR 2019] Gradient Matching Generative Networks for Zero-Shot Learning
- 3. 19ArXiv之ReID：Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person
- 4. 2019 CVPR之ReID:Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Id
- 5. 【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
- 6. 2019 CVPR：Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
- 7. 2020 CVPR 之ReID：AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identi
- 8. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 9. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
- 10. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification