Fan Z, Wu H, Fu X, et al. Residual-Guide Feature Fusion Network for Single Image Deraining[J]. arXiv preprint arXiv:1804.07493, 2018.
1. Overview
1.1. Motivation
- wasteful to utilize a resource-hungry model to meet all kinds of demands for rain streak removal task
- cascaded architecture may lost valuable intermediate reconstruction features
In this paper, it proposed ResGuidedNet
- residual generated from shallower blocks to guide deeper blocks
- coarse to fine estimation
- recursive convolutional
- apply to low-level and high-level
2. Methods
- recursive block. Conv+LeakyReLU, 5 recursive time
- ensemble all intermediate results to predict final output
2.1. Loss Function
- L2 + SSIM
- for block_k
- g. SSIM function
- λ=1
- M + 1 loss function
3. Experiments
3.1. Comparison
3.2. Ablation Study
3.3. Time
