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Related papers: A Dataset of Multi-Illumination Images in the Wild

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Single image scene relighting aims to generate a realistic new version of an input image so that it appears to be illuminated by a new target light condition. Although existing works have explored this problem from various perspectives,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Yixiong Yang , Hassan Ahmed Sial , Ramon Baldrich , Maria Vanrell

Deep image relighting is gaining more interest lately, as it allows photo enhancement through illumination-specific retouching without human effort. Aside from aesthetic enhancement and photo montage, image relighting is valuable for domain…

Computer Vision and Pattern Recognition · Computer Science 2020-05-14 Majed El Helou , Ruofan Zhou , Johan Barthas , Sabine Süsstrunk

We introduce OpenIllumination, a real-world dataset containing over 108K images of 64 objects with diverse materials, captured under 72 camera views and a large number of different illuminations. For each image in the dataset, we provide…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Isabella Liu , Linghao Chen , Ziyang Fu , Liwen Wu , Haian Jin , Zhong Li , Chin Ming Ryan Wong , Yi Xu , Ravi Ramamoorthi , Zexiang Xu , Hao Su

White balance (WB) correction in scenes with multiple illuminants remains a persistent challenge in computer vision. Recent methods explored fusion-based approaches, where a neural network linearly blends multiple sRGB versions of an input…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 David Serrano-Lozano , Aditya Arora , Luis Herranz , Konstantinos G. Derpanis , Michael S. Brown , Javier Vazquez-Corral

Existing methods for enhancing dark images captured in a very low-light environment assume that the intensity level of the optimal output image is known and already included in the training set. However, this assumption often does not hold,…

Image and Video Processing · Electrical Eng. & Systems 2023-04-05 Evgeny Hershkovitch Neiterman , Michael Klyuchka , Gil Ben-Artzi

Inverse rendering in urban scenes is pivotal for applications like autonomous driving and digital twins. Yet, it faces significant challenges due to complex illumination conditions, including multi-illumination and indirect light and shadow…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Jingjing Wang , Qirui Hu , Chong Bao , Yuke Zhu , Hujun Bao , Zhaopeng Cui , Guofeng Zhang

Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories. In contrast, the natural world is heavily imbalanced, as some species are more abundant and easier to…

Computer Vision and Pattern Recognition · Computer Science 2018-04-12 Grant Van Horn , Oisin Mac Aodha , Yang Song , Yin Cui , Chen Sun , Alex Shepard , Hartwig Adam , Pietro Perona , Serge Belongie

Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. Most learning-based low-light enhancement methods rely on paired training data captured under…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Maria Pilligua , David Serrano-Lozano , Pai Peng , Ramon Baldrich , Michael S. Brown , Javier Vazquez-Corral

Faithful manipulation of shape, material, and illumination in 2D Internet images would greatly benefit from a reliable factorization of appearance into material (i.e., diffuse and specular) and illumination (i.e., environment maps). On the…

Graphics · Computer Science 2017-11-15 Tuanfeng Y. Wang , Tobias Ritschel , Niloy J. Mitra

We present a new multi-sensor dataset for multi-view 3D surface reconstruction. It includes registered RGB and depth data from sensors of different resolutions and modalities: smartphones, Intel RealSense, Microsoft Kinect, industrial…

Imaging and perception in photon-limited scenarios is necessary for various applications, e.g., night surveillance or photography, high-speed photography, and autonomous driving. In these cases, cameras suffer from low signal-to-noise…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Bo Zhang , Yuchen Guo , Runzhao Yang , Zhihong Zhang , Jiayi Xie , Jinli Suo , Qionghai Dai

We present a collection of 24 multiple object scenes each recorded under 18 multiple light source illumination scenarios. The illuminants are varying in dominant spectral colours, intensity and distance from the scene. We mainly address the…

Computer Vision and Pattern Recognition · Computer Science 2020-03-27 Anna Smagina , Egor Ershov , Anton Grigoryev

We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-to-end relighting models are often limited by the scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Kai He , Ruofan Liang , Jacob Munkberg , Jon Hasselgren , Nandita Vijaykumar , Alexander Keller , Sanja Fidler , Igor Gilitschenski , Zan Gojcic , Zian Wang

The paper describes our experience collecting a new dataset for the light source estimation problem in a single image. The analysis of existing color targets is presented along with various technical and scientific aspects essential for…

Computer Vision and Pattern Recognition · Computer Science 2020-06-08 E. I. Ershov , A. V. Belokopytov , A. V. Savchik

Low-light image enhancement is challenging in that it needs to consider not only brightness recovery but also complex issues like color distortion and noise, which usually hide in the dark. Simply adjusting the brightness of a low-light…

Image and Video Processing · Electrical Eng. & Systems 2020-03-17 Feifan Lv , Yu Li , Feng Lu

Recent single-image relighting methods, powered by advanced generative models, have achieved impressive photorealism on synthetic benchmarks. However, their effectiveness in the complex visual landscape of the real world remains largely…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Lezhong Wang , Mehmet Onurcan Kaya , Siavash Bigdeli , Jeppe Revall Frisvad

In this paper, we study the problem of making brighter images from dark images found in the wild. The images are dark because they are taken in dim environments. They suffer from color shifts caused by quantization and from sensor noise. We…

Computer Vision and Pattern Recognition · Computer Science 2022-05-19 Sara Aghajanzadeh , David Forsyth

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. In this report we present…

Computer Vision and Pattern Recognition · Computer Science 2020-06-04 Alexandre Pierre Dherse , Martin Nicolas Everaert , Jakub Jan Gwizdała

Specular highlights are commonplace in images, however, methods for detecting them and in turn removing the phenomenon are particularly challenging. A reason for this, is due to the difficulty of creating a dataset for training or…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Mohamed Dahy Elkhouly , Theodore Tsesmelis , Alessio Del Bue , Stuart James

Wildlife monitoring is crucial to nature conservation and has been done by manual observations from motion-triggered camera traps deployed in the field. Widespread adoption of such in-situ sensors has resulted in unprecedented data volumes…

Computer Vision and Pattern Recognition · Computer Science 2020-09-25 Sayali Kulkarni , Tomer Gadot , Chen Luo , Tanya Birch , Eric Fegraus
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