Image Retouching
10 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Image Retouching
Most implemented papers
Deep Bilateral Learning for Real-Time Image Enhancement
google/hdrnet
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For this, we introduce a new neural network architecture inspired by bilateral grid processing and local affine color transforms.
Neural Color Operators for Sequential Image Retouching
The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar.
The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection
vlkniaz/MAGritte
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NeurIPS 2019
We collected large-scale manipulated image dataset to train our model.
Conditional Sequential Modulation for Efficient Global Image Retouching
hejingwenhejingwen/CSRNet
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ECCV 2020
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.
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
HuiZeng/Image-Adaptive-3DLUT
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The small CNN works on the down-sampled version of the input image to predict content-dependent weights to fuse the multiple basis 3D LUTs into an image-adaptive one, which is employed to transform the color and tone of source images efficiently.
Learning Diverse Tone Styles for Image Retouching
ssrheart/tsflow
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In particular, the style encoder predicts the target style representation of an input image, which serves as the conditional information in the RetouchNet for retouching, while the TSFlow maps the style representation vector into a Gaussian distribution in the forward pass.
RSFNet: A White-Box Image Retouching Approach using Region-Specific Color Filters
vicky0522/rsfnet
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ICCV 2023
Therefore, there is a need for white-box approaches that produce satisfying results and enable users to conveniently edit their images simultaneously.
Generalized Lightness Adaptation with Channel Selective Normalization
Existing methods typically work well on their trained lightness conditions but perform poorly in unknown ones due to their limited generalization ability.
WaveNet: Wave-Aware Image Enhancement
DeniJsonC/WaveNet
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The Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2023
In this paper, we formulate the enhancement into a signal modulation problem and propose the WaveNet architecture, which performs well in various parameters and improves the feature expression using wave-like feature representation.
Taming Lookup Tables for Efficient Image Retouching
Existing enhancement models often optimize for high performance while falling short of reducing hardware inference time and power consumption, especially on edge devices with constrained computing and storage resources.
