2019 CVPR之ReID：Joint Discriminative and Generative Learning for Person Re-identification
Joint Discriminative and Generative Learning for Person Re-identification 当前的问题及概述： 目前，ReID任务通过GAN网络训练越来越热门，然而，现有方法中的G途径与D再识别学习阶段相对独立。因此，reid模型通常直接对生成的数据进行训练。 本文提出了一个联合学习框架，将ReID任务和端到端的图像生成结合起来。提出的模型包
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相关文章
- 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 论文笔记
- 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