2018 IJCAI之ReID：Cross-Modality Person Re-Identification with Generative Adversarial Training

时间 2020-12-30

标签 GAN 多模态 ReID 深度学习人工智能繁體版

原文原文链接

Cross-Modality Person Re-Identification with Generative Adversarial Training 目前的问题：当前，面对这种跨模态问题，主要有两个困难： 1.RGB和红外模式之间缺乏识别同一人的区别信息 2.很难为这种大规模的交叉模式检索学习稳健的度量为了解决识别信息不足的问题，本文设计了一种基于前沿生成对抗训练的鉴别器来学习不同模式下的

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1. Face Aging with Contextual Generative Adversarial Nets
2. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
3. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
4. Boosting Adversarial Training with Hypersphere Embedding
5. Generative Adversarial Nets[CycleGAN]
6. Finding Tiny Faces in the Wild with Generative Adversarial Network
7. [cvpr2017]Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks
8. UNSUPERVISED REPRESENTATION LEARNING WITH DEEP CONVOLUTIONAL GENERATIVE ADVERSARIAL NETWORKS
9. IMPROVING GENERATIVE ADVERSARIAL NETWORKS WITH DENOISING FEATURE MATCHING（Bingio-ICLR2017）
10. Generative Adversarial Nets[BEGAN]

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