论文阅读：Dehaze-GLCGAN: Unpaired Single Image Dehazing Via Adversarial Training
目录 1. 摘要 2. 网络结构 2.1 整体结构 2.1 网络详情 1) 生成器 2) 判别器 3. 损失函数 3.1 对抗损失 3.2 循环一致性损失 3.3 颜色损失 3.4 循环感知损失 3.5 总损失 4. 读后感 1. 摘要 本文提出了一个名为Global-Local Cycle-consistent Generative Adversarial Network（Dehaze-
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相关文章
- 1. Single Image Dehazing via Conditional Generative Adversarial Network
- 2. 论文阅读《Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks》
- 3. 论文阅读：Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing
- 4. 论文阅读：Multi-scale Optimal Fusion model for single image dehazing
- 5. 论文阅读：FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
- 6. 【论文阅读】Domain Adaptation for Image Dehazing
- 7. 论文阅读：Non-Local Image Dehazing
- 8. 论文阅读笔记《GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training》
- 9. Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing
- 10. 论文阅读——Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network