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
Latest papers with no code
Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning
To perform effective collaborative modeling between image relighting and person ReID tasks, we integrate the multilevel feature interactions in CENet.
Personalized Video Relighting With an At-Home Light Stage
In this paper, we develop a personalized video relighting algorithm that produces high-quality and temporally consistent relit videos under any pose, expression, and lighting condition in real-time.
JoIN: Joint GANs Inversion for Intrinsic Image Decomposition
In this work, we propose to solve ill-posed inverse imaging problems using a bank of Generative Adversarial Networks (GAN) as a prior and apply our method to the case of Intrinsic Image Decomposition for faces and materials.
Neural-PBIR Reconstruction of Shape, Material, and Illumination
In the last stage, initialized by the neural predictions, we perform PBIR to refine the initial results and obtain the final high-quality reconstruction of object shape, material, and illumination.
ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
By leveraging the dataset, we perform an ablation study on the relighting capability of variants of the vanilla NeRF architecture and identify a lightweight architecture that can render novel views of an object under novel light conditions, which we use to establish a non-trivial baseline for the dataset.
Weakly-supervised Single-view Image Relighting
For re-rendering, we propose a differentiable specular rendering layer to render low-frequency non-Lambertian materials under various illuminations of spherical harmonics.
Relightable Neural Human Assets from Multi-view Gradient Illuminations
UltraStage will be publicly available to the community to stimulate significant future developments in various human modeling and rendering tasks.
DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated Images
Despite the success of existing traditional and deep learning-based methods, it is still challenging due to: (i) the requirement of three or more differently illuminated images, (ii) the inability to model unknown general reflectance, and (iii) the requirement of accurate 3D ground truth surface normals and known lighting information for training.
OutCast: Outdoor Single-image Relighting with Cast Shadows
We propose a relighting method for outdoor images.
SIRfyN: Single Image Relighting from your Neighbors
Novel theory shows that one can use similar scenes to estimate the different lightings that apply to a given scene, with bounded expected error.
