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Optical images of transparent three-dimensional objects can be different from a replica of the object's cross section in the image plane due to refraction at the surface or in the body of the object. Simulations of the object's image are…

In the conventional approach to lens imaging, rays are used to map object points to image points. However, many students have a need to think of the image as a whole. To answer this need, lens imaging is reinterpreted as a superposition of…

Physics Education · Physics 2016-01-20 Sascha Grusche

Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via fine-tuning, it also comes with fundamental disadvantages.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Julian Ost , Tanushree Banerjee , Mario Bijelic , Felix Heide

We analyze multi-bounce propagation of light in an unknown hidden volume and demonstrate that the reflected light contains sufficient information to recover the 3D structure of the hidden scene. We formulate the forward and inverse theory…

Estimating and modelling the appearance of an object under outdoor illumination conditions is a complex process. Although there have been several studies on illumination estimation and relighting, very few of them focus on estimating the…

Computer Vision and Pattern Recognition · Computer Science 2021-05-17 Farhan Rahman Wasee , Alen Joy , Charalambos Poullis

In this paper, we define a new problem of recovering the 3D geometry of an object confined in a transparent enclosure. We also propose a novel method for solving this challenging problem. Transparent enclosures pose challenges of multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Jinguang Tong , Sundaram Muthu , Fahira Afzal Maken , Chuong Nguyen , Hongdong Li

Humans can perceive scenes in 3D from a handful of 2D views. For AI agents, the ability to recognize a scene from any viewpoint given only a few images enables them to efficiently interact with the scene and its objects. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2021-12-03 Shengyi Qian , Alexander Kirillov , Nikhila Ravi , Devendra Singh Chaplot , Justin Johnson , David F. Fouhey , Georgia Gkioxari

A solution to the inversion problem of scattering would offer aberration-free diffraction-limited 3D images without the resolution and depth-of-field limitations of lens-based tomographic systems. Powerful algorithms are increasingly being…

Personalized image generation, where reference images of one or more subjects are used to generate their image according to a scene description, has gathered significant interest in the community. However, such generated images suffer from…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Parul Gupta , Abhinav Dhall , Thanh-Toan Do

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

Recent approaches to jointly reconstruct 3D humans and objects from a single RGB image represent 3D shapes with template-based or coarse models, which fail to capture details of loose clothing on human bodies. In this paper, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Ayushi Dutta , Marco Pesavento , Marco Volino , Adrian Hilton , Armin Mustafa

Our work aims to reconstruct hand-held objects given a single RGB image. In contrast to prior works that typically assume known 3D templates and reduce the problem to 3D pose estimation, our work reconstructs generic hand-held object…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Yufei Ye , Abhinav Gupta , Shubham Tulsiani

Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render highly specular objects, whose appearance varies quickly with changes in viewpoint. Recent works have improved NeRF's ability to render detailed specular appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Dor Verbin , Pratul P. Srinivasan , Peter Hedman , Ben Mildenhall , Benjamin Attal , Richard Szeliski , Jonathan T. Barron

This work presents a flexible system to reconstruct 3D models of objects captured with an RGB-D sensor. A major advantage of the method is that our reconstruction pipeline allows the user to acquire a full 3D model of the object. This is…

Computer Vision and Pattern Recognition · Computer Science 2015-05-22 Aitor Aldoma , Johann Prankl , Alexander Svejda , Markus Vincze

To endow machines with the ability to perceive the real-world in a three dimensional representation as we do as humans is a fundamental and long-standing topic in Artificial Intelligence. Given different types of visual inputs such as…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Bo Yang

Achieving aesthetically pleasing photography necessitates attention to multiple factors, including composition and capture conditions, which pose challenges to novices. Prior research has explored the enhancement of photo aesthetics…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Taichi Uchida , Yoshihiro Kanamori , Yuki Endo

A method for displaying volumetric images, which exploits our binocular vision and does not require eyewear, is discussed. The display can be rendered as a matrix of pivoting micromirrors irradiated by a light beam; each micromirror focuses…

Optics · Physics 2007-07-04 Oleg G. Semyonov

Taking an image of an object is at its core a lossy process. The rich information about the three-dimensional structure of the world is flattened to an image plane and decisions such as viewpoint and camera parameters are final and not…

Computer Vision and Pattern Recognition · Computer Science 2016-08-16 Konstantinos Rematas , Chuong Nguyen , Tobias Ritschel , Mario Fritz , Tinne Tuytelaars

We present an approach to infer a layer-structured 3D representation of a scene from a single input image. This allows us to infer not only the depth of the visible pixels, but also to capture the texture and depth for content in the scene…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Shubham Tulsiani , Richard Tucker , Noah Snavely

Existing methods for relightable view synthesis -- using a set of images of an object under unknown lighting to recover a 3D representation that can be rendered from novel viewpoints under a target illumination -- are based on inverse…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Xiaoming Zhao , Pratul P. Srinivasan , Dor Verbin , Keunhong Park , Ricardo Martin Brualla , Philipp Henzler