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All that structure from motion algorithms "see" are sets of 2D points. We show that these impoverished views of the world can be faked for the purpose of reconstructing objects in challenging settings, such as from a single image, or from a…

Computer Vision and Pattern Recognition · Computer Science 2014-11-25 João Carreira , Abhishek Kar , Shubham Tulsiani , Jitendra Malik

The reconstruction of three-dimensional dynamic scenes is a well-established yet challenging task within the domain of computer vision. In this paper, we propose a novel approach that combines the domains of 3D geometry reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 David Stotko , Reinhard Klein

This paper presents a novel framework to recover \emph{detailed} avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, texture, and viewpoints. Prior methods typically attempt to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-21 Hao Zhu , Xinxin Zuo , Haotian Yang , Sen Wang , Xun Cao , Ruigang Yang

Estimating object mass from visual input is challenging because mass depends jointly on geometric volume and material-dependent density, neither of which is directly observable from RGB appearance. Consequently, mass prediction from pixels…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Sungjae Lee , Junhan Jeong , Yeonjoo Hong , Kwang In Kim

Reconstructing the underlying 3D surface of an object from a single image is a challenging problem that has received extensive attention from the computer vision community. Many learning-based approaches tackle this problem by learning a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Nicolai Häni , Jun-Jee Chao , Volkan Isler

Reconstructing 3D geometry and appearance from a sparse set of fixed cameras is a foundational task with broad applications, yet it remains fundamentally constrained by the limited viewpoints. We show that this bound can be broken by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Ryosuke Hirai , Kohei Yamashita , Antoine Guédon , Ryo Kawahara , Vincent Lepetit , Ko Nishino

We present a novel framework to reconstruct complete 3D human shapes from a given target image by leveraging monocular unconstrained images. The objective of this work is to reproduce high-quality details in regions of the reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Marco Pesavento , Marco Volino , Adrian Hilton

Can computers perceive the physical properties of objects solely through vision? Research in cognitive science and vision science has shown that humans excel at identifying materials and estimating their physical properties based purely on…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Albert J. Zhai , Yuan Shen , Emily Y. Chen , Gloria X. Wang , Xinlei Wang , Sheng Wang , Kaiyu Guan , Shenlong Wang

Recovering the 3D structure of an object from a single image is a challenging task due to its ill-posed nature. One approach is to utilize the plentiful photos of the same object category to learn a strong 3D shape prior for the object.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Long-Nhat Ho , Anh Tuan Tran , Quynh Phung , Minh Hoai

An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application of canonical deep learning methods to regress from the…

Computer Vision and Pattern Recognition · Computer Science 2017-07-27 Rui Zhu , Hamed Kiani Galoogahi , Chaoyang Wang , Simon Lucey

Reconstructing 3D models from single-view images is a long-standing problem in computer vision. The latest advances for single-image 3D reconstruction extract a textual description from the input image and further utilize it to synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Yu Liu , Ruowei Wang , Jiaqi Li , Zixiang Xu , Qijun Zhao

Joint reconstruction of 3D human and object from a single image is an active research area, with pivotal applications in robotics and digital content creation. Despite recent advances, existing approaches suffer from two fundamental…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Hyeongjin Nam , Daniel Sungho Jung , Kyoung Mu Lee

We present a method that infers spatial arrangements and shapes of humans and objects in a globally consistent 3D scene, all from a single image in-the-wild captured in an uncontrolled environment. Notably, our method runs on datasets…

Computer Vision and Pattern Recognition · Computer Science 2020-08-21 Jason Y. Zhang , Sam Pepose , Hanbyul Joo , Deva Ramanan , Jitendra Malik , Angjoo Kanazawa

Most 3D reconstruction methods may only recover scene properties up to a global scale ambiguity. We present a novel approach to single view metrology that can recover the absolute scale of a scene represented by 3D heights of objects or…

Computer Vision and Pattern Recognition · Computer Science 2021-02-24 Rui Zhu , Xingyi Yang , Yannick Hold-Geoffroy , Federico Perazzi , Jonathan Eisenmann , Kalyan Sunkavalli , Manmohan Chandraker

3D reconstruction from 2D images is a central problem in computer vision. Recent works have been focusing on reconstruction directly from a single image. It is well known however that only one image cannot provide enough information for…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Anders Eriksson , Clinton Fookes , Sridha Sridharan , Simon Lucey

One challenge that remains open in 3D deep learning is how to efficiently represent 3D data to feed deep networks. Recent works have relied on volumetric or point cloud representations, but such approaches suffer from a number of issues…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Sridha Sridharan , Simon Lucey , Anders Eriksson , Clinton Fookes

This paper presents a multi stage 3D shape reconstruction system of multiple object scenes by considering the silhouette inconsistencies in shape-from silhouette SFS method. These inconsistencies are common in multiple view images due to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Waqqas-ur-Rehman Butt , Martin Servin

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

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or…

Computer Vision and Pattern Recognition · Computer Science 2017-04-04 Dimitrios Tzionas , Juergen Gall

Single-view 3D shape retrieval is a challenging task that is increasingly important with the growth of available 3D data. Prior work that has studied this task has not focused on evaluating how realistic occlusions impact performance, and…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Qirui Wu , Daniel Ritchie , Manolis Savva , Angel X. Chang