【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification
【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification 痛点 模型 实验 写作 参考文献 现有的大多数工作都是基于监督学习，而监督学习需要大量标注数据，严重限制了它的可拓展性。因而可迁移跨数据集的无监督模型被提出，且数据完全不需要标注。本文开发了一种基于非对称多任务字典学习的
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相关文章
- 1. 【ReID】【Skimming】Unity Style Transfer for Person Re-Identification
- 2. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
- 3. 【ReID】【skimming】SphereReID: Deep Hypersphere Manifold Embedding for Person Re-identification
- 4. 1610.Deep Learning Prototype Domains for Person Re-Identification-CUHK-SYSU-PRW 论文笔记
- 5. 【ReID】【Skimming】An Implicit Attention Mechanism for Deep Learning Pedestrian Re-identification Frame
- 6. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 论文笔记
- 7. CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-tempora
- 8. 《Deep Transfer Learning for Person Re-identification》-阅读笔记
- 9. Person Transfer GAN to Bridge Domain Gap for Person Re-identification
- 10. 【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification