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Related papers: Deconstruction of compound objects from image sets

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We investigate the problem of estimating the 3D shape of an object, given a set of 2D landmarks in a single image. To alleviate the reconstruction ambiguity, a widely-used approach is to confine the unknown 3D shape within a shape space…

Computer Vision and Pattern Recognition · Computer Science 2015-06-03 Xiaowei Zhou , Spyridon Leonardos , Xiaoyan Hu , Kostas Daniilidis

Joint camera pose and dense geometry estimation from a set of images or a monocular video remains a challenging problem due to its computational complexity and inherent visual ambiguities. Most dense incremental reconstruction systems…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Kirill Mazur , Gwangbin Bae , Andrew J. Davison

Patterns, which are collections of elements arranged in regular or near-regular arrangements, are an important graphic art form and widely used due to their elegant simplicity and aesthetic appeal. When a pattern is encoded as a flat image…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Pradyumna Reddy , Paul Guerrero , Matt Fisher , Wilmot Li , Miloy J. Mitra

We consider the problem of obtaining dense 3D reconstructions of humans from single and partially occluded views. In such cases, the visual evidence is usually insufficient to identify a 3D reconstruction uniquely, so we aim at recovering…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Benjamin Biggs , Sébastien Ehrhadt , Hanbyul Joo , Benjamin Graham , Andrea Vedaldi , David Novotny

The reflection superposition phenomenon is complex and widely distributed in the real world, which derives various simplified linear and nonlinear formulations of the problem. In this paper, based on the investigation of the weaknesses of…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Qiming Hu , Xiaojie Guo

We present a new end-to-end learning framework to obtain detailed and spatially coherent reconstructions of multiple people from a single image. Existing multi-person methods suffer from two main drawbacks: they are often model-based and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Armin Mustafa , Akin Caliskan , Lourdes Agapito , Adrian Hilton

3D geometry is a very informative cue when interacting with and navigating an environment. This writing proposes a new approach to 3D reconstruction and scene understanding, which implicitly learns 3D geometry from depth maps pairing a deep…

Computer Vision and Pattern Recognition · Computer Science 2018-08-22 Dario Rethage , Federico Tombari , Felix Achilles , Nassir Navab

Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-08 Kuldeep Purohit , Subeesh Vasu , M. Purnachandra Rao , A. N. Rajagopalan

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

We describe a method to parse a complex, cluttered indoor scene into primitives which offer a parsimonious abstraction of scene structure. Our primitives are simple convexes. Our method uses a learned regression procedure to parse a scene…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Vaibhav Vavilala , David Forsyth

This paper presents an explore-and-classify framework for structured architectural reconstruction from an aerial image. Starting from a potentially imperfect building reconstruction by an existing algorithm, our approach 1) explores the…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Fuyang Zhang , Xiang Xu , Nelson Nauata , Yasutaka Furukawa

The reconstruction of shredded documents consists of coherently arranging fragments of paper (shreds) to recover the original document(s). A great challenge in computational reconstruction is to properly evaluate the compatibility between…

Computer Vision and Pattern Recognition · Computer Science 2020-07-03 Thiago M. Paixão , Rodrigo F. Berriel , Maria C. S. Boeres , Alessandro L. Koerich , Claudine Badue , Alberto F. de Souza , Thiago Oliveira-Santos

In this work, we focus on the task of learning and representing dense correspondences in deformable object categories. While this problem has been considered before, solutions so far have been rather ad-hoc for specific object types (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2020-11-26 Natalia Neverova , David Novotny , Vasil Khalidov , Marc Szafraniec , Patrick Labatut , Andrea Vedaldi

This paper presents a new system to obtain dense object reconstructions along with 6-DoF poses from a single image. Geared towards high fidelity reconstruction, several recent approaches leverage implicit surface representations and deep…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Aniket Pokale , Aditya Aggarwal , K. Madhava Krishna

This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point clouds, or mesh surfaces, we aim to recover 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2020-05-29 Xin Chen , Yuwei Li , Xi Luo , Tianjia Shao , Jingyi Yu , Kun Zhou , Youyi Zheng

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

Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decomposing a target object from a complex background is…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Jun Wu , Sicheng Li , Sihui Ji , Yifei Yang , Yue Wang , Rong Xiong , Yiyi Liao

Many man-made objects have intrinsic symmetries and Manhattan structure. By assuming an orthographic projection model, this paper addresses the estimation of 3D structures and camera projection using symmetry and/or Manhattan structure…

Computer Vision and Pattern Recognition · Computer Science 2017-03-30 Yuan Gao , Alan L. Yuille

The problem of decomposing non-manifold object has already been studied in solid modeling. However, the few proposed solutions are limited to the problem of decomposing solids described through their boundaries. In this thesis we study the…

Graphics · Computer Science 2019-04-03 Franco Morando

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
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