A Cascaded Convolutional Neural Network for Single Image Dehazing
1 模型设计 post-processing：对网络估计出的传播图又用了导向滤波器进行后续的优化 2 训练 数据集 NYU-V2 Depth dataset 前提：(1)全局大气光B服从[0.7.1]均匀分布;（2）大气散射系数从[0.6，2.8]随机选择；（3）针对每个无雾清晰图像以及对应的深度图，我们随机选择5个全局大气感和大气散射系数，人工合成有雾图像；（4）所有样本采样到207x154的大
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相关文章
- 1. A mixed-scale dense convolutional neural network for image analysis
- 2. LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation
- 3. A Model-driven Deep Neural Network for Single Image Rain Removal阅读分享
- 4. 总结Deep Convolutional Neural Network for Image Deconvolution
- 5. Single Image Dehazing via Conditional Generative Adversarial Network
- 6. 论文笔记_S2D.21_Deep Convolutional Neural Fields for Depth Estimation from a Single Image
- 7. Deep Convolutional Neural Fields for Depth Estimation from a Single Image
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- 9. Tensorflow - Implement for a Convolutional Neural Network on MNIST.
- 10. 论文阅读：FFA-Net: Feature Fusion Attention Network for Single Image Dehazing