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Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem. In this paper, we propose an efficient method to reconstruct the scene's 3D geometry and reflectance from…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Rui Li , Guangmin Zang , Miao Qi , Wolfgang Heidrich

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

Reconstructing the shape and appearance of real-world objects using measured 2D images has been a long-standing problem in computer vision. In this paper, we introduce a new analysis-by-synthesis technique capable of producing high-quality…

Computer Vision and Pattern Recognition · Computer Science 2021-06-28 Fujun Luan , Shuang Zhao , Kavita Bala , Zhao Dong

While the problem of estimating shapes and diffuse reflectances of human faces from images has been extensively studied, there is relatively less work done on recovering the specular albedo. This paper presents a lightweight solution for…

Computer Vision and Pattern Recognition · Computer Science 2019-11-28 Guoxian Song , Jianmin Zheng , Jianfei Cai , Tat-Jen Cham

Multi-view inverse rendering aims to recover geometry, materials, and illumination consistently across multiple viewpoints. When applied to multi-view images, existing single-view approaches often ignore cross-view relationships, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Xiangzuo Wu , Chengwei Ren , Jun Zhou , Xiu Li , Yuan Liu

Reconstructing an object's high-quality 3D shape with inherent spectral reflectance property, beyond typical device-dependent RGB albedos, opens the door to applications requiring a high-fidelity 3D model in terms of both geometry and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Chunyu Li , Yusuke Monno , Masatoshi Okutomi

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

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

360-degree images offer a significantly wider field of view compared to traditional pinhole cameras, enabling sparse sampling and dense 3D reconstruction in low-texture environments. This makes them crucial for applications in VR, AR, and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zhongmiao Yan , Qi Wu , Songpengcheng Xia , Junyuan Deng , Xiang Mu , Renbiao Jin , Ling Pei

We propose a neural inverse rendering approach that jointly reconstructs geometry, spatially varying reflectance, and lighting conditions from multi-view images captured under varying directional lighting. Unlike prior multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Xu Cao , Takafumi Taketomi

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

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

This work tackles the challenging task of achieving real-time novel view synthesis for reflective surfaces across various scenes. Existing real-time rendering methods, especially those based on meshes, often have subpar performance in…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Chaojie Ji , Yufeng Li , Yiyi Liao

In this work, we propose an inverse rendering model that estimates 3D shape, spatially-varying reflectance, homogeneous subsurface scattering parameters, and an environment illumination jointly from only a pair of captured images of a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Chenhao Li , Trung Thanh Ngo , Hajime Nagahara

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

We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , David Kriegman , Ravi Ramamoorthi

Inverse rendering seeks to recover 3D geometry, surface material, and lighting from captured images, enabling advanced applications such as novel-view synthesis, relighting, and virtual object insertion. However, most existing techniques…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Chih-Hao Lin , Jia-Bin Huang , Zhengqin Li , Zhao Dong , Christian Richardt , Tuotuo Li , Michael Zollhöfer , Johannes Kopf , Shenlong Wang , Changil Kim

We propose a novel method to reconstruct the 3D shapes of transparent objects using hand-held captured images under natural light conditions. It combines the advantage of explicit mesh and multi-layer perceptron (MLP) network, a hybrid…

Computer Vision and Pattern Recognition · Computer Science 2023-03-30 Jiamin Xu , Zihan Zhu , Hujun Bao , Weiwei Xu

We are witnessing an explosion of neural implicit representations in computer vision and graphics. Their applicability has recently expanded beyond tasks such as shape generation and image-based rendering to the fundamental problem of…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Jiaming Sun , Xi Chen , Qianqian Wang , Zhengqi Li , Hadar Averbuch-Elor , Xiaowei Zhou , Noah Snavely
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