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We investigate the problem of estimating the 3D shape of an object defined by a set of 3D landmarks, given their 2D correspondences in a single image. A successful approach to alleviating the reconstruction ambiguity is the 3D deformable…

Computer Vision and Pattern Recognition · Computer Science 2017-01-12 Xiaowei Zhou , Menglong Zhu , Spyridon Leonardos , Kostas Daniilidis

In this paper a semi-supervised deep framework is proposed for the problem of 3D shape inverse rendering from a single 2D input image. The main structure of proposed framework consists of unsupervised pre-trained components which…

Computer Vision and Pattern Recognition · Computer Science 2017-11-17 Shima Kamyab , S. Zohreh Azimifar

We present Neural Reflectance Fields, a novel deep scene representation that encodes volume density, normal and reflectance properties at any 3D point in a scene using a fully-connected neural network. We combine this representation with a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-18 Sai Bi , Zexiang Xu , Pratul Srinivasan , Ben Mildenhall , Kalyan Sunkavalli , Miloš Hašan , Yannick Hold-Geoffroy , David Kriegman , Ravi Ramamoorthi

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

Accurately measuring the geometry and spatially-varying reflectance of real-world objects is a complex task due to their intricate shapes formed by concave features, hollow engravings and diverse surfaces, resulting in inter-reflection and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Jing Yang , Pratusha Bhuvana Prasad , Qing Zhang , Yajie Zhao

We introduce Patchwork, a new general-purpose shape representation capable of modeling 2D and 3D geometry with a small number of parameters. Patchwork is grounded in a rigorous mathematical framework, providing provable complexity bounds…

Graphics · Computer Science 2026-05-19 Ruichen Zheng , Biao Zhang , Michael Birsak , Mikhail Skopenkov , Peter Wonka

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

This paper introduces a versatile paradigm for integrating multi-view reflectance (optional) and normal maps acquired through photometric stereo. Our approach employs a pixel-wise joint re-parameterization of reflectance and normal,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Baptiste Brument , Robin Bruneau , Yvain Quéau , Jean Mélou , François Bernard Lauze , Jean-Denis , Jean-Denis Durou , Lilian Calvet

3D reconstruction from a single RGB image is a challenging problem in computer vision. Previous methods are usually solely data-driven, which lead to inaccurate 3D shape recovery and limited generalization capability. In this work, we focus…

Computer Vision and Pattern Recognition · Computer Science 2020-06-18 Yichao Zhou , Shichen Liu , Yi Ma

We introduce a high resolution spatially adaptive light source, or a projector, into a neural reflectance field that allows to both calibrate the projector and photo realistic light editing. The projected texture is fully differentiable…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Yotam Erel , Daisuke Iwai , Amit H. Bermano

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

Neural 3D scene representations have shown great potential for 3D reconstruction from 2D images. However, reconstructing real-world captures of complex scenes still remains a challenge. Existing generic 3D reconstruction methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Fangjinhua Wang , Marie-Julie Rakotosaona , Michael Niemeyer , Richard Szeliski , Marc Pollefeys , Federico Tombari

In this talk we present and discuss a new general approach to the synthesis of metasurfaces for full control of transmitted and reflected fields. The method is based on the use of an equivalent impedance matrix which connects the tangential…

Optics · Physics 2016-03-24 V. Asadchy , M. Albooyeh , S. Tcvetkova , Y. Ra'di , S. A. Tretyakov

Geometry reconstruction of textureless, non-Lambertian objects under unknown natural illumination (i.e., in the wild) remains challenging as correspondences cannot be established and the reflectance cannot be expressed in simple analytical…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Kohei Yamashita , Shohei Nobuhara , Ko Nishino

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

We introduce a novel learning-based method for encoding and manipulating 3D surface meshes. Our method is specifically designed to create an interpretable embedding space for deformable shape collections. Unlike previous 3D mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Sara Hahner , Souhaib Attaiki , Jochen Garcke , Maks Ovsjanikov

We present a method for compositing virtual objects into a photograph such that the object colors appear to have been processed by the photo's camera imaging pipeline. Compositing in such a camera-aware manner is essential for high realism,…

Computer Vision and Pattern Recognition · Computer Science 2019-03-28 Jun Gao , Xiao Li , Liwei Wang , Sanja Fidler , Stephen Lin

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical images (whether focused by lenses or not) are diffraction…

Optics · Physics 2021-04-08 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta

We present a robust method to find region-level correspondences between shapes, which are invariant to changes in geometry and applicable across multiple shape representations. We generate simplified shape graphs by jointly decomposing the…

Graphics · Computer Science 2018-03-06 Yanir Kleiman , Maks Ovsjanikov

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