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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

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

Most 3D face reconstruction methods rely on 3D morphable models, which disentangle the space of facial deformations into identity geometry, expressions and skin reflectance. These models are typically learned from a limited number of 3D…

Computer Vision and Pattern Recognition · Computer Science 2020-10-06 Mallikarjun B R , Ayush Tewari , Hans-Peter Seidel , Mohamed Elgharib , Christian Theobalt

This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model…

Neural and Evolutionary Computing · Computer Science 2009-12-14 Vincy Joseph , Shalini Bhatia

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

Modeling outdoor scenes for the synthetic 3D environment requires the recovery of reflectance/albedo information from raw images, which is an ill-posed problem due to the complicated unmodeled physics in this process (e.g., indirect…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Shuang Song , Rongjun Qin

In this study, we introduce a novel two-stage technique for decomposing and reconstructing facial features from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual. To…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Daisheng Jin , Jiangbei Hu , Baixin Xu , Yuxin Dai , Chen Qian , Ying He

We present a differentiable ray-tracing based novel face reconstruction approach where scene attributes - 3D geometry, reflectance (diffuse, specular and roughness), pose, camera parameters, and scene illumination - are estimated from…

Computer Vision and Pattern Recognition · Computer Science 2021-01-15 Abdallah Dib , Gaurav Bharaj , Junghyun Ahn , Cédric Thébault , Philippe-Henri Gosselin , Marco Romeo , Louis Chevallier

Recovering the 3D geometry of a purely texture-less object with generally unknown surface reflectance (e.g. non-Lambertian) is regarded as a challenging task in multi-view reconstruction. The major obstacle revolves around establishing…

Computer Vision and Pattern Recognition · Computer Science 2021-05-26 Ziang Cheng , Hongdong Li , Yuta Asano , Yinqiang Zheng , Imari Sato

We present a novel strategy to automatically reconstruct 3D faces from monocular images with explicitly disentangled facial geometry (pose, identity and expression), reflectance (diffuse and specular albedo), and self-shadows. The scene…

Computer Vision and Pattern Recognition · Computer Science 2019-10-14 Abdallah Dib , Gaurav Bharaj , Junghyun Ahn , Cedric Thebault , Philippe-Henri Gosselin , Louis Chevallier

Reconstructing high-fidelity 3D facial texture from a single image is a quite challenging task due to the lack of complete face information and the domain gap between the 3D face and 2D image. Further, obtaining re-renderable 3D faces has…

Computer Vision and Pattern Recognition · Computer Science 2022-06-07 Mingxin Yang , Jianwei Guo , Zhanglin Cheng , Xiaopeng Zhang , Dong-Ming Yan

Modeling non-Lambertian effects such as facial specularity leads to a more realistic 3D Morphable Face Model. Existing works build parametric models for diffuse and specular albedo using Light Stage data. However, only diffuse and specular…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Yuxuan Han , Zhibo Wang , Feng Xu

Recovering surface albedos from photogrammetric images for realistic rendering and synthetic environments can greatly facilitate its downstream applications in VR/AR/MR and digital twins. The textured 3D models from standard photogrammetric…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Shuang Song , Rongjun Qin

Traditional methods for image-based 3D face reconstruction and facial motion retargeting fit a 3D morphable model (3DMM) to the face, which has limited modeling capacity and fail to generalize well to in-the-wild data. Use of deformation…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Bindita Chaudhuri , Noranart Vesdapunt , Linda Shapiro , Baoyuan Wang

We propose a novel biophysical and dichromatic reflectance model that efficiently characterises spectral skin reflectance. We show how to fit the model to multispectral face images enabling high quality estimation of diffuse and specular…

Computer Vision and Pattern Recognition · Computer Science 2019-02-19 Sarah Alotaibi , William A. P. Smith

Recovering detailed facial geometry from a set of calibrated multi-view images is valuable for its wide range of applications. Traditional multi-view stereo (MVS) methods adopt an optimization-based scheme to regularize the matching cost.…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Yunze Xiao , Hao Zhu , Haotian Yang , Zhengyu Diao , Xiangju Lu , Xun Cao

Achieving high-fidelity 3D surface reconstruction while preserving fine details remains challenging, especially in the presence of materials with complex reflectance properties and without a dense-view setup. In this paper, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Robin Bruneau , Baptiste Brument , Yvain Quéau , Jean Mélou , François Bernard Lauze , Jean-Denis Durou , Lilian Calvet

This paper addresses the problem of mirror surface reconstruction, and proposes a solution based on observing the reflections of a moving reference plane on the mirror surface. Unlike previous approaches which require tedious calibration,…

Computer Vision and Pattern Recognition · Computer Science 2021-01-26 Kai Han , Miaomiao Liu , Dirk Schnieders , Kwan-Yee K. Wong

We address the problem of recovering the 3D geometry of a human face from a set of facial images in multiple views. While recent studies have shown impressive progress in 3D Morphable Model (3DMM) based facial reconstruction, the settings…

Computer Vision and Pattern Recognition · Computer Science 2019-04-10 Fanzi Wu , Linchao Bao , Yajing Chen , Yonggen Ling , Yibing Song , Songnan Li , King Ngi Ngan , Wei Liu

Shape from Polarization (SfP) estimates surface normals using photos captured at different polarizer rotations. Fundamentally, the SfP model assumes that light is reflected either diffusely or specularly. However, this model is not valid…

Computer Vision and Pattern Recognition · Computer Science 2016-06-14 Vage Taamazyan , Achuta Kadambi , Ramesh Raskar
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