Exploiting Diffusion Prior for Generalizable Dense Prediction
Contents generated by recent advanced Text-to-Image (T2I) diffusion models are sometimes
too imaginative for existing off-the-shelf dense predictors to estimate due to the immitigable …
too imaginative for existing off-the-shelf dense predictors to estimate due to the immitigable …
Estimating reflectance layer from a single image: Integrating reflectance guidance and shadow/specular aware learning
Estimating the reflectance layer from a single image is a challenging task. It becomes more
challenging when the input image contains shadows or specular highlights, which often …
challenging when the input image contains shadows or specular highlights, which often …
Intrinsic image decomposition via ordinal shading
Intrinsic decomposition is a fundamental mid-level vision problem that plays a crucial role in
various inverse rendering and computational photography pipelines. Generating highly …
various inverse rendering and computational photography pipelines. Generating highly …
A decoupled multi-task network for shadow removal
Shadow removal, which aims to restore the illumination in shadow regions, is challenging
due to the diversity of shadows in terms of location, intensity, shape, and size. Different from …
due to the diversity of shadows in terms of location, intensity, shape, and size. Different from …
Intrinsicdiffusion: Joint intrinsic layers from latent diffusion models
Reasoning about the intrinsic properties of an image, such as albedo, illumination, and
surface geometry, is a long-standing problem with many applications in image editing and …
surface geometry, is a long-standing problem with many applications in image editing and …
Exploiting Diffusion Prior for Generalizable Dense Prediction
Contents generated by recent advanced Text-to-Image (T2I) diffusion models are sometimes
too imaginative for existing off-the-shelf dense predictors to estimate due to the immitigable …
too imaginative for existing off-the-shelf dense predictors to estimate due to the immitigable …
IDTransformer: Transformer for Intrinsic Image Decomposition
The aim of intrinsic image decomposition (IID) is to recover reflectance and the shading from
a given image. As different combinations are possible, IID is an under constrained problem …
a given image. As different combinations are possible, IID is an under constrained problem …
Retinex-diffusion: On controlling illumination conditions in diffusion models via retinex theory
This paper introduces a novel approach to illumination manipulation in diffusion models,
addressing the gap in conditional image generation with a focus on lighting conditions. We …
addressing the gap in conditional image generation with a focus on lighting conditions. We …
A general albedo recovery approach for aerial photogrammetric images through inverse rendering
Modeling outdoor scenes for the synthetic 3D environment requires the recovery of
reflectance/albedo information from raw images, which is an ill-posed problem due to the …
reflectance/albedo information from raw images, which is an ill-posed problem due to the …
Intrinsic Appearance Decomposition Using Point Cloud Representation
X Xing, K Groh, S Karaoglu… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
The aim of intrinsic decomposition is to deduce the albedo and shading components,
typically from 2D images. However, this task is ill-posed, necessitating previous methods to …
typically from 2D images. However, this task is ill-posed, necessitating previous methods to …