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
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising
Unfortunately, Monte Carlo integration provides estimates with significant noise, even at large sample counts, which makes gradient-based inverse rendering very challenging.
Designing An Illumination-Aware Network for Deep Image Relighting
nk-cs-zzl/ian
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Lighting is a determining factor in photography that affects the style, expression of emotion, and even quality of images.
NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illumination
FuxiComputerVision/Nefii
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CVPR 2023
Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images.
Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark
StanfordORB/Stanford-ORB
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NeurIPS 2023
We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark.
Intrinsic Harmonization for Illumination-Aware Compositing
compphoto/IntrinsicCompositing
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Despite significant advancements in network-based image harmonization techniques, there still exists a domain disparity between typical training pairs and real-world composites encountered during inference.
