A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal

11/24/2018
by   Huangxing Lin, et al.
0

Existing methods for single images raindrop removal either have poor robustness or suffer from parameter burdens. In this paper, we propose a new Adjacent Aggregation Network (A^2Net) with lightweight architectures to remove raindrops from single images. Instead of directly cascading convolutional layers, we design an adjacent aggregation architecture to better fuse features for rich representations generation, which can lead to high quality images reconstruction. To further simplify the learning process, we utilize a problem-specific knowledge to force the network focus on the luminance channel in the YUV color space instead of all RGB channels. By combining adjacent aggregating operation with color space transformation, the proposed A^2Net can achieve state-of-the-art performances on raindrop removal with significant parameters reduction.

READ FULL TEXT

page 1

page 4

page 5

page 6

page 7

page 8

research
03/03/2021

Non-local Channel Aggregation Network for Single Image Rain Removal

Rain streaks showing in images or videos would severely degrade the perf...
research
08/30/2022

CAIR: Fast and Lightweight Multi-Scale Color Attention Network for Instagram Filter Removal

Image restoration is an important and challenging task in computer visio...
research
05/16/2018

Lightweight Pyramid Networks for Image Deraining

Existing deep convolutional neural networks have found major success in ...
research
01/25/2018

C2MSNet: A Novel approach for single image haze removal

Degradation of image quality due to the presence of haze is a very commo...
research
02/23/2018

Adaptive specular reflection detection and inpainting in colonoscopy video frames

Colonoscopy video frames might be contaminated by bright spots with unsa...
research
08/27/2022

LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal

This paper focuses on the limitations of current over-parameterized shad...
research
11/21/2018

A Deep Tree-Structured Fusion Model for Single Image Deraining

We propose a simple yet effective deep tree-structured fusion model base...

Please sign up or login with your details

Forgot password? Click here to reset