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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

Image of a scene captured through a piece of transparent and reflective material, such as glass, is often spoiled by a superimposed layer of reflection image. While separating the reflection from a familiar object in an image is mentally…

Computer Vision and Pattern Recognition · Computer Science 2018-02-02 Zhixiang Chi , Xiaolin Wu , Xiao Shu , Jinjin Gu

Representing 3D objects and scenes with neural radiance fields has become very popular over the last years. Recently, surface-based representations have been proposed, that allow to reconstruct 3D objects from simple photographs. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Sarthak Gupta , Patrik Huber

One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and…

Computer Vision and Pattern Recognition · Computer Science 2018-11-15 Chuhang Zou , Ruiqi Guo , Zhizhong Li , Derek Hoiem

Spatial relationships between objects provide important information for text-based image retrieval. As users are more likely to describe a scene from a real world perspective, using 3D spatial relationships rather than 2D relationships that…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Ang Li , Jin Sun , Joe Yue-Hei Ng , Ruichi Yu , Vlad I. Morariu , Larry S. Davis

The reflections caused by common semi-reflectors, such as glass windows, can impact the performance of computer vision algorithms. State-of-the-art methods can remove reflections on synthetic data and in controlled scenarios. However, they…

Computer Vision and Pattern Recognition · Computer Science 2018-08-17 Patrick Wieschollek , Orazio Gallo , Jinwei Gu , Jan Kautz

Actions as simple as grasping an object or navigating around it require a rich understanding of that object's 3D shape from a given viewpoint. In this paper we repurpose powerful learning machinery, originally developed for object…

Computer Vision and Pattern Recognition · Computer Science 2015-11-26 Shubham Tulsiani , Abhishek Kar , Qixing Huang , João Carreira , Jitendra Malik

The gaze of a person tends to reflect their interest. This work explores what happens when this statement is taken literally and applied to robots. Here we present a robot system that employs a moving robot head with a screen-based eye…

Robotics · Computer Science 2025-11-05 Matti Krüger , Daniel Tanneberg , Chao Wang , Stephan Hasler , Michael Gienger

The reflectance field of a face describes the reflectance properties responsible for complex lighting effects including diffuse, specular, inter-reflection and self shadowing. Most existing methods for estimating the face reflectance from a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Mallikarjun B R. , Ayush Tewari , Tae-Hyun Oh , Tim Weyrich , Bernd Bickel , Hans-Peter Seidel , Hanspeter Pfister , Wojciech Matusik , Mohamed Elgharib , Christian Theobalt

Curved refractive objects are common in the human environment, and have a complex visual appearance that can cause robotic vision algorithms to fail. Light-field cameras allow us to address this challenge by capturing the view-dependent…

Robotics · Computer Science 2021-04-20 Dorian Tsai , Peter Corke , Thierry Peynot , Donald G. Dansereau

A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, and recover these structures from 3D and 2D images via…

Computer Vision and Pattern Recognition · Computer Science 2018-06-20 Danilo Jimenez Rezende , S. M. Ali Eslami , Shakir Mohamed , Peter Battaglia , Max Jaderberg , Nicolas Heess

We explain theoretically how to reconstruct the 3D scene from successive frames in order to see the video in 3D. To do this, features, associated to moving rigid objects in 3D, are extracted in frames and matched. The vanishing point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-30 Slimane Larabi

Humans can easily understand a single image as depicting multiple potential objects permitting interaction. We use this skill to plan our interactions with the world and accelerate understanding new objects without engaging in interaction.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-09 Shengyi Qian , David F. Fouhey

We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-conditioned inverse rendering problems, and are as such unable…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Xiaoyan Xing , Philipp Henzler , Junhwa Hur , Runze Li , Jonathan T. Barron , Pratul P. Srinivasan , Dor Verbin

3D Gaussian Splatting shows great potential in reconstructing photo-realistic 3D scenes. However, these methods typically bake illumination into their representations, limiting their use for physically-based rendering and scene editing.…

Graphics · Computer Science 2025-04-03 Zirui Wu , Jianteng Chen , Laijian Li , Shaoteng Wu , Zhikai Zhu , Kang Xu , Martin R. Oswald , Jie Song

Reconstructing object geometry and material from multiple views typically requires optimization. Differentiable path tracing is an appealing framework as it can reproduce complex appearance effects. However, it is difficult to use due to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Purvi Goel , Loudon Cohen , James Guesman , Vikas Thamizharasan , James Tompkin , Daniel Ritchie

We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera. Our method leverages motion…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Yu-Lun Liu , Wei-Sheng Lai , Ming-Hsuan Yang , Yung-Yu Chuang , Jia-Bin Huang

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

The ability to see around corners, i.e., recover details of a hidden scene from its reflections in the surrounding environment, is of considerable interest in a wide range of applications. However, the diffuse nature of light reflected from…

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle the problem, we propose a coarse-to-fine method to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-14 Zhongguo Li , Magnus Oskarsson , Anders Heyden
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