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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

Computer vision applications have heavily relied on the linear combination of Lambertian diffuse and microfacet specular reflection models for representing reflected radiance, which turns out to be physically incompatible and limited in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Tomoki Ichikawa , Yoshiki Fukao , Shohei Nobuhara , Ko Nishino

Reflective surfaces present a persistent challenge for reliable 3D mapping and perception in robotics and autonomous systems. However, existing reflection datasets and benchmarks remain limited to sparse 2D data. This paper introduces the…

Robotics · Computer Science 2024-03-12 Xiting Zhao , Sören Schwertfeger

Reflection removal technology plays a crucial role in photography and computer vision applications. However, existing techniques are hindered by the lack of high-quality in-the-wild datasets. In this paper, we propose a novel paradigm for…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Kangning Yang , Ling Ouyang , Huiming Sun , Jie Cai , Lan Fu , Jiaming Ding , Chiu Man Ho , Zibo Meng

Physically-based rendering (PBR) is key for immersive rendering effects used widely in the industry to showcase detailed realistic scenes from computer graphics assets. A well-known caveat is that producing the same is computationally heavy…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Jing Yang , Hanyuan Xiao , Wenbin Teng , Yunxuan Cai , Yajie Zhao

Light interreflections occurring in a concave object generate a color gradient which is characteristic of the object's spectral reflectance. In this paper, we use this property in order to estimate the spectral reflectance of matte,…

Computer Vision and Pattern Recognition · Computer Science 2018-07-04 Rada Deeb , Damien Muselet , Mathieu Hebert , Alain Tremeau

We present a fast and simple technique to convert images into a radiance surface-based scene representation. Building on existing radiance volume reconstruction algorithms, we introduce a subtle yet impactful modification of the loss…

We present a novel method of simulating wave effects in graphics using ray--based renderers with a new function: the Wave BSDF (Bidirectional Scattering Distribution Function). Reflections from neighboring surface patches represented by…

Graphics · Computer Science 2011-01-31 Tom Cuypers , Se Baek Oh , Tom Haber , Philippe Bekaert , Ramesh Raskar

A vast majority of augmented reality devices come equipped with depth and color cameras. Despite their advantages, extracting both photometric and depth features simultaneously in real-time remains challenging due to inherent differences…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Mehfuz A Rahman , Khushal Das , Jiju Poovvancheri , Neil London , Dong Chen

We present a method to estimate an HDR environment map from a narrow field-of-view LDR camera image in real-time. This enables perceptually appealing reflections and shading on virtual objects of any material finish, from mirror to diffuse,…

Computer Vision and Pattern Recognition · Computer Science 2021-07-29 Gowri Somanath , Daniel Kurz

Inverse rendering seeks to reconstruct both geometry and spatially varying BRDFs (SVBRDFs) from captured images. To address the inherent ill-posedness of inverse rendering, basis BRDF representations are commonly used, modeling SVBRDFs as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Hoon-Gyu Chung , Seokjun Choi , Seung-Hwan Baek

We propose a material acquisition approach to recover the spatially-varying BRDF and normal map of a near-planar surface from a single image captured by a handheld mobile phone camera. Our method images the surface under arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2018-04-17 Zhengqin Li , Kalyan Sunkavalli , Manmohan Chandraker

Accurately evaluating the quality of bidirectional reflectance distribution function (BRDF) models is essential for photo-realistic rendering. Traditional BRDF-space metrics often employ numerical error measures that fail to capture…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Behnaz Kavoosighafi , Rafal K. Mantiuk , Saghi Hajisharif , Ehsan Miandji , Jonas Unger

In this paper, we introduce a technique to estimate measured BRDFs from a sparse set of samples. Our approach offers accurate BRDF reconstructions that are generalizable to new materials. This opens the door to BDRF reconstructions from a…

Illumination estimation is often used in mixed reality to re-render a scene from another point of view, to change the color/texture of an object, or to insert a virtual object consistently lit into a real video or photograph. Specifically,…

Computer Vision and Pattern Recognition · Computer Science 2018-12-13 Grégoire Nieto , Salma Jiddi , Philippe Robert

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

We present a novel convolutional neural network architecture for photometric stereo (Woodham, 1980), a problem of recovering 3D object surface normals from multiple images observed under varying illuminations. Despite its long history in…

Computer Vision and Pattern Recognition · Computer Science 2018-05-30 Tatsunori Taniai , Takanori Maehara

A method to obtain three-dimensional data of real-world objects by integrating their material properties is presented. The material properties are defined by capturing the Reflectance Fields of the real-world objects. It is shown, unlike…

Computer Vision and Pattern Recognition · Computer Science 2012-03-15 Maria-Luisa Sosas , Miguel-Octavio Arias

We present a learning-based technique for estimating high dynamic range (HDR), omnidirectional illumination from a single low dynamic range (LDR) portrait image captured under arbitrary indoor or outdoor lighting conditions. We train our…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Chloe LeGendre , Wan-Chun Ma , Rohit Pandey , Sean Fanello , Christoph Rhemann , Jason Dourgarian , Jay Busch , Paul Debevec

Transparent objects are widely used in our daily lives, making it important to teach robots to interact with them. However, it's not easy because the reflective and refractive effects can make depth cameras fail to give accurate geometry…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Tutian Tang , Jiyu Liu , Jieyi Zhang , Haoyuan Fu , Wenqiang Xu , Cewu Lu