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Related papers: IllumiNet: Transferring Illumination from Planar S…

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This paper presents a process for estimating the spatially varying surface reflectance of complex scenes observed under natural illumination. In contrast to previous methods, our process is not limited to scenes viewed under controlled…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Alen Joy , Charalambos Poullis

We propose a novel inverse rendering method that enables the transformation of existing indoor panoramas with new indoor furniture layouts under natural illumination. To achieve this, we captured indoor HDR panoramas along with real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Guanzhou Ji , Azadeh O. Sawyer , Srinivasa G. Narasimhan

We introduce LumiNet, a novel architecture that leverages generative models and latent intrinsic representations for effective lighting transfer. Given a source image and a target lighting image, LumiNet synthesizes a relit version of the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Xiaoyan Xing , Konrad Groh , Sezer Karaoglu , Theo Gevers , Anand Bhattad

Relighting is an essential step in realistically transferring objects from a captured image into another environment. For example, authentic telepresence in Augmented Reality requires faces to be displayed and relit consistent with the…

Computer Vision and Pattern Recognition · Computer Science 2020-04-21 Thomas Nestmeyer , Jean-François Lalonde , Iain Matthews , Andreas M. Lehrmann

Low light images captured in a non-uniform illumination environment usually are degraded with the scene depth and the corresponding environment lights. This degradation results in severe object information loss in the degraded image…

Computer Vision and Pattern Recognition · Computer Science 2020-08-03 Xin Xu , Shiqin Wang , Zheng Wang , Xiaolong Zhang , Ruimin Hu

Inverse rendering, the process of inferring scene properties from images, is a challenging inverse problem. The task is ill-posed, as many different scene configurations can give rise to the same image. Most existing solutions incorporate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Linjie Lyu , Ayush Tewari , Marc Habermann , Shunsuke Saito , Michael Zollhöfer , Thomas Leimkühler , Christian Theobalt

Alignment between real and virtual objects is a challenging task required for the deployment of Mixed Reality (MR) into manufacturing, medical, and construction applications. To face this challenge, a series of methods have been proposed.…

Human-Computer Interaction · Computer Science 2022-11-17 Alejandro Martin-Gomez , Alexander Winkler , Rafael de la Tijera Obert , Javad Fotouhi , Daniel Roth , Ulrich Eck , Nassir Navab

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

We present InvRGB+L, a novel inverse rendering model that reconstructs large, relightable, and dynamic scenes from a single RGB+LiDAR sequence. Conventional inverse graphics methods rely primarily on RGB observations and use LiDAR mainly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Xiaoxue Chen , Bhargav Chandaka , Chih-Hao Lin , Ya-Qin Zhang , David Forsyth , Hao Zhao , Shenlong Wang

We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis. The goal of our method is to generate photo-realistic re-renderings of reconstructed objects for…

Computer Vision and Pattern Recognition · Computer Science 2020-01-16 Justus Thies , Michael Zollhöfer , Christian Theobalt , Marc Stamminger , Matthias Nießner

Image retrieval under varying illumination conditions, such as day and night images, is addressed by image preprocessing, both hand-crafted and learned. Prior to extracting image descriptors by a convolutional neural network, images are…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Tomas Jenicek , Ondřej Chum

There is widespread interest in estimating the fluorescence properties of natural materials in an image. However, the separation between reflected and fluoresced components is difficult, because it is impossible to distinguish reflected and…

Computer Vision and Pattern Recognition · Computer Science 2016-05-16 Henryk Blasinski , Joyce Farrell , Brian Wandell

It is suggested that low-light image enhancement realizes one-to-many mapping since we have different definitions of NORMAL-light given application scenarios or users' aesthetic. However, most existing methods ignore subjectivity of the…

Computer Vision and Pattern Recognition · Computer Science 2021-01-05 Ya'nan Wang , Zhuqing Jiang , Chang Liu , Kai Li , Aidong Men , Haiying Wang

Capturing and labeling camera images in the real world is an expensive task, whereas synthesizing labeled images in a simulation environment is easy for collecting large-scale image data. However, learning from only synthetic images may not…

Computer Vision and Pattern Recognition · Computer Science 2018-07-06 Tadanobu Inoue , Subhajit Chaudhury , Giovanni De Magistris , Sakyasingha Dasgupta

We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance model within a volumetric setting by treating each sample along…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Alexander Mai , Dor Verbin , Falko Kuester , Sara Fridovich-Keil

In this paper, we study the problem of reproducing the world lighting from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the…

Computer Vision and Pattern Recognition · Computer Science 2014-12-30 Zhengdong Zhang , Phillip Isola , Edward H. Adelson

Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Hadi Alzayer , Philipp Henzler , Jonathan T. Barron , Jia-Bin Huang , Pratul P. Srinivasan , Dor Verbin

Despite significant advances in algorithms and hardware, global illumination continues to be a challenge in the real-time domain. Time constraints often force developers to either compromise on the quality of global illumination or…

Graphics · Computer Science 2024-06-13 Alexandr Kuznetsov , Stavros Diolatzis , Anton Sochenov , Anton Kaplanyan

Mixed Reality (MR) headsets promise a future of immersive telepresence where virtual humans blend indistinguishably into real or virtual surroundings. Achieving this vision requires a method for capturing a user's motion, estimating…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Jianchun Chen , Yinda Zhang , Rohit Pandey , Thabo Beeler , Marc Habermann , Christian Theobalt

Distinguishing visually similar objects like forged/authentic bills and healthy/unhealthy plants is beyond the capabilities of even the most sophisticated classifiers. We propose the use of multiplexed illumination to extend the range of…

Computer Vision and Pattern Recognition · Computer Science 2021-02-24 Taihua Wang , Donald G. Dansereau
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