Image Relighting
25 papers with code • 2 benchmarks • 3 datasets
Image relighting involves changing the illumination settings of an image.
Benchmarks
These leaderboards are used to track progress in Image Relighting
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Libraries
Use these libraries to find Image Relighting models and implementations
VIDIT
Stanford-ORB
Dynamic OLAT Dataset
Most implemented papers
Scale-recurrent Network for Deep Image Deblurring
jiangsutx/SRN-Deblur
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CVPR 2018
In single image deblurring, the "coarse-to-fine" scheme, i. e. gradually restoring the sharp image on different resolutions in a pyramid, is very successful in both traditional optimization-based methods and recent neural-network-based approaches.
NTIRE 2021 Depth Guided Image Relighting Challenge
In this paper, we review the NTIRE 2021 depth guided image relighting challenge.
VIDIT: Virtual Image Dataset for Illumination Transfer
Deep image relighting is gaining more interest lately, as it allows photo enhancement through illumination-specific retouching without human effort.
AIM 2020: Scene Relighting and Illumination Estimation Challenge
The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i. e., light source position).
Multi-modal Bifurcated Network for Depth Guided Image Relighting
weitingchen83/NTIRE2021-Depth-Guided-Image-Relighting-MBNet
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This model extracts the image and the depth features by the bifurcated network in the encoder.
Extracting Triangular 3D Models, Materials, and Lighting From Images
NVlabs/nvdiffrec
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CVPR 2022
We present an efficient method for joint optimization of topology, materials and lighting from multi-view image observations.
Local Relighting of Real Scenes
We introduce the task of local relighting, which changes a photograph of a scene by switching on and off the light sources that are visible within the image.
0.5 Petabyte Simulation of a 45-Qubit Quantum Circuit
Near-term quantum computers will soon reach sizes that are challenging to directly simulate, even when employing the most powerful supercomputers.
GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing
proteus1991/GridDehazeNet
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ICCV 2019
The proposed hazing method does not rely on the atmosphere scattering model, and we provide an explanation as to why it is not necessarily beneficial to take advantage of the dimension reduction offered by the atmosphere scattering model for image dehazing, even if only the dehazing results on synthetic images are concerned.
Scene relighting with illumination estimation in the latent space on an encoder-decoder scheme
martin-ev/2DSceneRelighting
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The image relighting task of transferring illumination conditions between two images offers an interesting and difficult challenge with potential applications in photography, cinematography and computer graphics.
