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We present a new color photometric stereo (CPS) method that recovers high quality, detailed 3D face geometry in a single shot. Our system uses three uncalibrated near point lights of different colors and a single camera. For robust…

Computer Vision and Pattern Recognition · Computer Science 2019-12-24 Zhang Chen , Yu Ji , Mingyuan Zhou , Sing Bing Kang , Jingyi Yu

Human re-rendering from a single image is a starkly under-constrained problem, and state-of-the-art algorithms often exhibit undesired artefacts, such as over-smoothing, unrealistic distortions of the body parts and garments, or implausible…

Computer Vision and Pattern Recognition · Computer Science 2021-01-12 Kripasindhu Sarkar , Dushyant Mehta , Weipeng Xu , Vladislav Golyanik , Christian Theobalt

Images of static scenes submerged beneath a wavy water surface exhibit severe non-rigid distortions. The physics of water flow suggests that water surfaces possess spatio-temporal smoothness and temporal periodicity. Hence they possess a…

Computer Vision and Pattern Recognition · Computer Science 2019-08-07 Jerin Geo James , Pranay Agrawal , Ajit Rajwade

With the developments of dual-lens camera modules,depth information representing the third dimension of thecaptured scenes becomes available for smartphones. It isestimated by stereo matching algorithms, taking as input thetwo views…

Computer Vision and Pattern Recognition · Computer Science 2018-09-27 Ruichao Xiao , Wenxiu Sun , Jiahao Pang , Qiong Yan , Jimmy Ren

Photometric stereo is a method that seeks to reconstruct the normal vectors of an object from a set of images of the object illuminated under different light sources. While effective in some situations, classical photometric stereo relies…

Computer Vision and Pattern Recognition · Computer Science 2018-08-09 Andrew J. Wagenmaker , Brian E. Moore , Raj Rao Nadakuditi

We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simultaneously denoise the 3D poses and geometries of all objects…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Manuel Dahnert , Angela Dai , Norman Müller , Matthias Nießner

Demands on capturing dynamic scenes of underwater environments are rapidly growing. Passive stereo is applicable to capture dynamic scenes, however the shape with textureless surfaces or irregular reflections cannot be recovered by the…

Computer Vision and Pattern Recognition · Computer Science 2018-08-28 Kazuto Ichimaru , Ryo Furukawa , Hiroshi Kawasaki

Underwater images are altered by the physical characteristics of the medium through which light rays pass before reaching the optical sensor. Scattering and wavelength-dependent absorption significantly modify the captured colors depending…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Clémentin Boittiaux , Ricard Marxer , Claire Dune , Aurélien Arnaubec , Maxime Ferrera , Vincent Hugel

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

Despite significant progress made in the past few years, challenges remain for depth estimation using a single monocular image. First, it is nontrivial to train a metric-depth prediction model that can generalize well to diverse scenes…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Wei Yin , Jianming Zhang , Oliver Wang , Simon Niklaus , Simon Chen , Yifan Liu , Chunhua Shen

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

Existing vision systems for autonomous driving or robots are sensitive to waterdrops adhered to windows or camera lenses. Most recent waterdrop removal approaches take a single image as input and often fail to recover the missing content…

Computer Vision and Pattern Recognition · Computer Science 2021-08-10 Zifan Shi , Na Fan , Dit-Yan Yeung , Qifeng Chen

We present ReFlow, a unified framework for monocular dynamic scene reconstruction that learns 3D motion in a novel self-correction manner from raw video. Existing methods often suffer from incomplete scene initialization for dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Yanzhe Liang , Ruijie Zhu , Hanzhi Chang , Zhuoyuan Li , Jiahao Lu , Tianzhu Zhang

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

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Petr Hruby , Tomas Pajdla

In this paper, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon lidar…

Image and Video Processing · Electrical Eng. & Systems 2021-02-03 Quentin Legros , Julian Tachella , Rachael Tobin , Aongus McCarthy , Sylvain Meignen , Gerald S. Buller , Yoann Altmann , Stephen McLaughlin , Michael E. Davies

Volumetric scene reconstruction from a single image is crucial for a broad range of applications like autonomous driving and robotics. Recent volumetric reconstruction methods achieve impressive results, but generally require expensive 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Philipp Wulff , Felix Wimbauer , Dominik Muhle , Daniel Cremers

Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth shift induced by shift-invariant reconstruction losses used in…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Wei Yin , Jianming Zhang , Oliver Wang , Simon Niklaus , Long Mai , Simon Chen , Chunhua Shen

Eliminating reflections caused by incident light interacting with reflective medium remains an ill-posed problem in the image restoration area. The primary challenge arises from the overlapping of reflection and transmission components in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Pengbo Guo , Chengxu Liu , Guoshuai Zhao , Xingsong Hou , Jialie Shen , Xueming Qian

In this paper, we present a new compositing approach to obtain stylized reflections and refractions with a simple control. Our approach does not require any mask or separate 3D rendering. Moreover, only one additional image is sufficient to…

Graphics · Computer Science 2024-01-05 Ergun Akleman , Youyou Wang , Ozgur Gonen
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