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Inferring the scene illumination from a single image is an essential yet challenging task in computer vision and computer graphics. Existing works estimate lighting by regressing representative illumination parameters or generating…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Fangneng Zhan , Yingchen Yu , Changgong Zhang , Rongliang Wu , Wenbo Hu , Shijian Lu , Feiying Ma , Xuansong Xie , Ling Shao

Accurate lighting estimation is challenging yet critical to many computer vision and computer graphics tasks such as high-dynamic-range (HDR) relighting. Existing approaches model lighting in either frequency domain or spatial domain which…

Computer Vision and Pattern Recognition · Computer Science 2021-06-25 Fangneng Zhan , Changgong Zhang , Wenbo Hu , Shijian Lu , Feiying Ma , Xuansong Xie , Ling Shao

This paper addresses the task of estimating the light arriving from all directions to a 3D point observed at a selected pixel in an RGB image. This task is challenging because it requires predicting a mapping from a partial scene…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Shuran Song , Thomas Funkhouser

We present a method to estimate lighting from a single image of an indoor scene. Previous work has used an environment map representation that does not account for the localized nature of indoor lighting. Instead, we represent lighting as a…

Computer Vision and Pattern Recognition · Computer Science 2019-10-22 Marc-André Gardner , Yannick Hold-Geoffroy , Kalyan Sunkavalli , Christian Gagné , Jean-François Lalonde

Estimating a scene's lighting is a very important task when compositing synthetic content within real environments, with applications in mixed reality and post-production. In this work we present a data-driven model that estimates an HDR…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Vasileios Gkitsas , Nikolaos Zioulis , Federico Alvarez , Dimitrios Zarpalas , Petros Daras

We present a method for estimating lighting from a single perspective image of an indoor scene. Previous methods for predicting indoor illumination usually focus on either simple, parametric lighting that lack realism, or on richer…

Computer Vision and Pattern Recognition · Computer Science 2022-11-11 Henrique Weber , Mathieu Garon , Jean-François Lalonde

Global illumination (GI) is essential for realistic rendering but remains computationally expensive due to the complexity of simulating indirect light transport. Recent neural methods have mainly relied on per-scene optimization, sometimes…

Graphics · Computer Science 2025-10-22 Bing Xu , Mukund Varma T , Cheng Wang , Tzumao Li , Lifan Wu , Bartlomiej Wronski , Ravi Ramamoorthi , Marco Salvi

We propose an automatic method to infer high dynamic range illumination from a single, limited field-of-view, low dynamic range photograph of an indoor scene. In contrast to previous work that relies on specialized image capture, user…

Computer Vision and Pattern Recognition · Computer Science 2017-11-22 Marc-André Gardner , Kalyan Sunkavalli , Ersin Yumer , Xiaohui Shen , Emiliano Gambaretto , Christian Gagné , Jean-François Lalonde

In this work, we propose a step towards a more accurate prediction of the environment light given a single picture of a known object. To achieve this, we developed a deep learning method that is able to encode the latent space of indoor…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Henrique Weber , Donald Prévost , Jean-François Lalonde

Because of the diversity in lighting environments, existing illumination estimation techniques have been designed explicitly on indoor or outdoor environments. Methods have focused specifically on capturing accurate energy (e.g., through…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Mohammad Reza Karimi Dastjerdi , Jonathan Eisenmann , Yannick Hold-Geoffroy , Jean-François Lalonde

We present a scheme for fast environment light estimation from the RGBD appearance of individual objects and their local image areas. Conventional inverse rendering is too computationally demanding for real-time applications, and the…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Xin Wei , Guojun Chen , Yue Dong , Stephen Lin , Xin Tong

Accurate lighting estimation is a significant yet challenging task in computer vision and graphics. However, existing methods either struggle to restore detailed textures of illumination map, or face challenges in running speed and texture…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Kunliang Xie

Illuminant estimation plays a key role in digital camera pipeline system, it aims at reducing color casting effect due to the influence of non-white illuminant. Recent researches handle this task by using Convolution Neural Network (CNN) as…

Computer Vision and Pattern Recognition · Computer Science 2019-02-14 Yongjie Liu , Sijie Shen

Recent advances in neural rendering have shown great potential for reconstructing scenes from multiview images. However, accurately representing objects with glossy surfaces remains a challenge for existing methods. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ruofan Liang , Huiting Chen , Chunlin Li , Fan Chen , Selvakumar Panneer , Nandita Vijaykumar

Lighting prediction from a single image is becoming increasingly important in many vision and augmented reality (AR) applications in which shading and shadow consistency between virtual and real objects should be guaranteed. However, this…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Jiayang Bai , Jie Guo , Chenchen Wan , Zhenyu Chen , Zhen He , Shan Yang , Piaopiao Yu , Yan Zhang , Yanwen Guo

Manipulating the illumination of a 3D scene within a single image represents a fundamental challenge in computer vision and graphics. This problem has traditionally been addressed using inverse rendering techniques, which involve explicit…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Shrisha Bharadwaj , Haiwen Feng , Giorgio Becherini , Victoria Fernandez Abrevaya , Michael J. Black

We propose an efficient lighting estimation pipeline that is suitable to run on modern mobile devices, with comparable resource complexities to state-of-the-art mobile deep learning models. Our pipeline, PointAR, takes a single RGB-D image…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Yiqin Zhao , Tian Guo

We consider the challenging problem of outdoor lighting estimation for the goal of photorealistic virtual object insertion into photographs. Existing works on outdoor lighting estimation typically simplify the scene lighting into an…

Computer Vision and Pattern Recognition · Computer Science 2022-08-22 Zian Wang , Wenzheng Chen , David Acuna , Jan Kautz , Sanja Fidler

Manipulating the light source of given images is an interesting task and useful in various applications, including photography and cinematography. Existing methods usually require additional information like the geometric structure of the…

Computer Vision and Pattern Recognition · Computer Science 2020-10-16 Li-Wen Wang , Wan-Chi Siu , Zhi-Song Liu , Chu-Tak Li , Daniel P. K. Lun

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
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