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Related papers: WildLight: In-the-wild Inverse Rendering with a Fl…

200 papers

We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment. Multiview reconstruction of reflective objects is extremely…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Yuan Liu , Peng Wang , Cheng Lin , Xiaoxiao Long , Jiepeng Wang , Lingjie Liu , Taku Komura , Wenping Wang

Intrinsic image decomposition, which is an essential task in computer vision, aims to infer the reflectance and shading of the scene. It is challenging since it needs to separate one image into two components. To tackle this, conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-05-28 Yunfei Liu , Yu Li , Shaodi You , Feng Lu

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

Being able to see beyond the direct line of sight is an intriguing prospective and could benefit a wide variety of important applications. Recent work has demonstrated that time-resolved measurements of indirect diffuse light contain…

Graphics · Computer Science 2019-10-24 Julian Iseringhausen , Matthias B. Hullin

Inverse rendering aims at recovering both geometry and materials of objects. It provides a more compatible reconstruction for conventional rendering engines, compared with the neural radiance fields (NeRFs). On the other hand, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Haoyuan Wang , Wenbo Hu , Lei Zhu , Rynson W. H. Lau

We develop a method that recovers the surface, materials, and illumination of a scene from its posed multi-view images. In contrast to prior work, it does not require any additional data and can handle glossy objects or bright lighting. It…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yue Fan , Ningjing Fan , Ivan Skorokhodov , Oleg Voynov , Savva Ignatyev , Evgeny Burnaev , Peter Wonka , Yiqun Wang

Recovering the 3D shape of transparent objects using a small number of unconstrained natural images is an ill-posed problem. Complex light paths induced by refraction and reflection have prevented both traditional and deep multiview stereo…

Computer Vision and Pattern Recognition · Computer Science 2020-07-24 Zhengqin Li , Yu-Ying Yeh , Manmohan Chandraker

We present a learning-based method to infer plausible high dynamic range (HDR), omnidirectional illumination given an unconstrained, low dynamic range (LDR) image from a mobile phone camera with a limited field of view (FOV). For training…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Chloe LeGendre , Wan-Chun Ma , Graham Fyffe , John Flynn , Laurent Charbonnel , Jay Busch , Paul Debevec

Optical-resolution fluorescence imaging through and within complex samples presents a significant challenge due to random light scattering, with substantial implications across multiple fields. While significant advancements in coherent…

Optics · Physics 2023-12-27 Gil Weinberg , Elad Sunray , Ori Katz

We present SfSNet, an end-to-end learning framework for producing an accurate decomposition of an unconstrained human face image into shape, reflectance and illuminance. SfSNet is designed to reflect a physical lambertian rendering model.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-20 Soumyadip Sengupta , Angjoo Kanazawa , Carlos D. Castillo , David Jacobs

Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, requiring high quality synthetic renderings to train a…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Ye Yu , Abhimitra Meka , Mohamed Elgharib , Hans-Peter Seidel , Christian Theobalt , William A. P. Smith

In this work, we use multi-view aerial images to reconstruct the geometry, lighting, and material of facades using neural signed distance fields (SDFs). Without the requirement of complex equipment, our method only takes simple RGB images…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zixuan Xie , Rengan Xie , Rong Li , Kai Huang , Pengju Qiao , Jingsen Zhu , Xu Yin , Qi Ye , Wei Hua , Yuchi Huo , Hujun Bao

Recent neural rendering methods have demonstrated accurate view interpolation by predicting volumetric density and color with a neural network. Although such volumetric representations can be supervised on static and dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Julian Knodt , Joe Bartusek , Seung-Hwan Baek , Felix Heide

Mixed Reality scene relighting, where virtual changes to lighting conditions realistically interact with physical objects, producing authentic illumination and shadows, can be used in a variety of applications. One such application in real…

Graphics · Computer Science 2025-08-22 Hanwen Zhao , John Akers , Baback Elmieh , Ira Kemelmacher-Shlizerman

We propose a novel method for high-quality facial texture reconstruction from RGB images using a novel capturing routine based on a single smartphone which we equip with an inexpensive polarization foil. Specifically, we turn the flashlight…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Dejan Azinović , Olivier Maury , Christophe Hery , Mathias Nießner , Justus Thies

Methods for 3D reconstruction such as Photometric stereo recover the shape and reflectance properties using multiple images of an object taken with variable lighting conditions from a fixed viewpoint. Photometric stereo assumes that a scene…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Anish R. Khadka , Paolo Remagnino , Vasileios Argyriou

We present a deep learning approach to reconstruct scene appearance from unstructured images captured under collocated point lighting. At the heart of Deep Reflectance Volumes is a novel volumetric scene representation consisting of…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , Miloš Hašan , Yannick Hold-Geoffroy , David Kriegman , Ravi Ramamoorthi

In this paper we are extracting surface reflectance and natural environmental illumination from a reflectance map, i.e. from a single 2D image of a sphere of one material under one illumination. This is a notoriously difficult problem, yet…

Computer Vision and Pattern Recognition · Computer Science 2016-03-29 Stamatios Georgoulis , Konstantinos Rematas , Tobias Ritschel , Mario Fritz , Luc Van Gool , Tinne Tuytelaars

Estimating and modelling the appearance of an object under outdoor illumination conditions is a complex process. Although there have been several studies on illumination estimation and relighting, very few of them focus on estimating the…

Computer Vision and Pattern Recognition · Computer Science 2021-05-17 Farhan Rahman Wasee , Alen Joy , Charalambos Poullis

A concept of light-fields computed from multiple view images on regular grids has proven its benefit for scene representations, and supported realistic renderings of novel views and photographic effects such as refocusing and shallow depth…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Hyunjun Jung , Hae-Gon Jeon