Conditional Sequential Modulation for Efficient Global Image Retouching

09/22/2020
by   Jingwen He, et al.
0

Photo retouching aims at enhancing the aesthetic visual quality of images that suffer from photographic defects such as over/under exposure, poor contrast, inharmonious saturation. Practically, photo retouching can be accomplished by a series of image processing operations. In this paper, we investigate some commonly-used retouching operations and mathematically find that these pixel-independent operations can be approximated or formulated by multi-layer perceptrons (MLPs). Based on this analysis, we propose an extremely light-weight framework - Conditional Sequential Retouching Network (CSRNet) - for efficient global image retouching. CSRNet consists of a base network and a condition network. The base network acts like an MLP that processes each pixel independently and the condition network extracts the global features of the input image to generate a condition vector. To realize retouching operations, we modulate the intermediate features using Global Feature Modulation (GFM), of which the parameters are transformed by condition vector. Benefiting from the utilization of 1×1 convolution, CSRNet only contains less than 37k trainable parameters, which is orders of magnitude smaller than existing learning-based methods. Extensive experiments show that our method achieves state-of-the-art performance on the benchmark MIT-Adobe FiveK dataset quantitively and qualitatively. Code is available at https://github.com/hejingwenhejingwen/CSRNet.

READ FULL TEXT

page 2

page 11

page 13

research
04/13/2021

Very Lightweight Photo Retouching Network with Conditional Sequential Modulation

Photo retouching aims at improving the aesthetic visual quality of image...
research
05/31/2022

Cascade Luminance and Chrominance for Image Retouching: More Like Artist

Photo retouching aims to adjust the luminance, contrast, and saturation ...
research
05/07/2021

Toward Interactive Modulation for Photo-Realistic Image Restoration

Modulating image restoration level aims to generate a restored image by ...
research
03/11/2021

Diverse Semantic Image Synthesis via Probability Distribution Modeling

Semantic image synthesis, translating semantic layouts to photo-realisti...
research
09/21/2023

MEFLUT: Unsupervised 1D Lookup Tables for Multi-exposure Image Fusion

In this paper, we introduce a new approach for high-quality multi-exposu...
research
03/22/2022

Focal Modulation Networks

In this work, we propose focal modulation network (FocalNet in short), w...
research
03/08/2022

Dual Lottery Ticket Hypothesis

Fully exploiting the learning capacity of neural networks requires overp...

Please sign up or login with your details

Forgot password? Click here to reset