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We propose a new technique for estimating spatially varying parametric materials from a single image of an object with unknown shape in unknown illumination. Our method uses a low-order parametric reflectance model, and incorporates strong…

Graphics · Computer Science 2019-12-30 Kevin Karsch , David Forsyth

3D reconstruction aims to recover the dense 3D structure of a scene. It plays an essential role in various applications such as Augmented/Virtual Reality (AR/VR), autonomous driving and robotics. Leveraging multiple views of a scene…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Fangjinhua Wang , Qingtian Zhu , Di Chang , Quankai Gao , Junlin Han , Tong Zhang , Richard Hartley , Marc Pollefeys

Inverse rendering aims to estimate physical attributes of a scene, e.g., reflectance, geometry, and lighting, from image(s). Inverse rendering has been studied primarily for single objects or with methods that solve for only one of the…

Computer Vision and Pattern Recognition · Computer Science 2019-09-17 Soumyadip Sengupta , Jinwei Gu , Kihwan Kim , Guilin Liu , David W. Jacobs , Jan Kautz

This paper introduces a novel method for detailed 3D shape reconstruction utilizing thermal polarization cues. Unlike state-of-the-art methods, the proposed approach is independent of illumination and material properties. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Takahiro Kushida , Kenichiro Tanaka

Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to recover the detailed surface geometry, where the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Lu Sang , Bjoern Haefner , Xingxing Zuo , Daniel Cremers

A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the world from flat, 2D images of that world. Traditional methods for recovering scene properties such as shape, reflectance, or illumination rely…

Computer Vision and Pattern Recognition · Computer Science 2020-10-09 Jonathan T. Barron , Jitendra Malik

Inverse rendering pipelines are gaining prominence in realizing photo-realistic reconstruction of real-world objects for emulating them in virtual reality scenes. Apart from material reflectances, spectral rendering and in-scene…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Parisha Joshi , Daljit Singh J. Dhillon

We present MIRReS, a novel two-stage inverse rendering framework that jointly reconstructs and optimizes the explicit geometry, material, and lighting from multi-view images. Unlike previous methods that rely on implicit irradiance fields…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Yuxin Dai , Qi Wang , Jingsen Zhu , Dianbing Xi , Yuchi Huo , Chen Qian , Ying He

Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagation and attenuation, perspective viewing geometry and…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Fotios Logothetis , Roberto Mecca , Ignas Budvytis , Roberto Cipolla

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable many applications such as relighting and virtual object insertion. Recent NeRF based methods achieve impressive fidelity of 3D reconstruction, but bake…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zian Wang , Tianchang Shen , Jun Gao , Shengyu Huang , Jacob Munkberg , Jon Hasselgren , Zan Gojcic , Wenzheng Chen , Sanja Fidler

Three-dimensional reconstruction of objects from shading information is a challenging task in computer vision. As most of the approaches facing the Photometric Stereo problem use simplified far-field assumptions, real-world scenarios have…

Computer Vision and Pattern Recognition · Computer Science 2021-10-13 Roberto Mecca , Fotios Logothetis , Ignas Budvytis , Roberto Cipolla

In this work, we propose a novel method for the detailed reconstruction of transparent objects by exploiting polarimetric cues. Most of the existing methods usually lack sufficient constraints and suffer from the over-smooth problem. Hence,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-26 Mingqi Shao , Chongkun Xia , Dongxu Duan , Xueqian Wang

Most indoor 3D scene reconstruction methods focus on recovering 3D geometry and scene layout. In this work, we go beyond this to propose PhotoScene, a framework that takes input image(s) of a scene along with approximately aligned CAD…

Computer Vision and Pattern Recognition · Computer Science 2022-07-05 Yu-Ying Yeh , Zhengqin Li , Yannick Hold-Geoffroy , Rui Zhu , Zexiang Xu , Miloš Hašan , Kalyan Sunkavalli , Manmohan Chandraker

This study explores the use of photometric techniques (shape-from-shading and uncalibrated photometric stereo) for upsampling the low-resolution depth map from an RGB-D sensor to the higher resolution of the companion RGB image. A…

Computer Vision and Pattern Recognition · Computer Science 2019-06-26 Bjoern Haefner , Songyou Peng , Alok Verma , Yvain Quéau , Daniel Cremers

We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very challenging task, which is ill-suited for general-purpose…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Zongcheng Li , Xiaoxiao Long , Yusen Wang , Tuo Cao , Wenping Wang , Fei Luo , Chunxia Xiao

In this paper, we propose a novel method for joint recovery of camera pose, object geometry and spatially-varying Bidirectional Reflectance Distribution Function (svBRDF) of 3D scenes that exceed object-scale and hence cannot be captured…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Carolin Schmitt , Božidar Antić , Andrei Neculai , Joo Ho Lee , Andreas Geiger

Inverse rendering aims to reconstruct geometry and reflectance of objects from images. Despite recent progress, existing methods often produces inaccurate reconstructions that are sensitive to ambient illumination conditions. Here we…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Hoon-Gyu Chung , Jinnyeong Kim , Hyunwoo Kang , Seung-Hwan Baek

Implicit neural representation has opened up new possibilities for inverse rendering. However, existing implicit neural inverse rendering methods struggle to handle strongly illuminated scenes with significant shadows and indirect…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Yanzhen Chen , Xinyu Gao , Yazhen Yuan , Yu Wu , Xiaowei Zhou , Xiaogang Jin

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or…

Computer Vision and Pattern Recognition · Computer Science 2017-04-04 Dimitrios Tzionas , Juergen Gall

The challenge of image-based 3D reconstruction for glossy objects lies in separating diffuse and specular components on glossy surfaces from captured images, a task complicated by the ambiguity in discerning lighting conditions and material…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Bojian Wu , Yifan Peng , Ruizhen Hu , Xiaowei Zhou
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