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We propose an approach for 3D reconstruction and segmentation of a single object placed on a flat surface from an input video. Our approach is to perform dense depth map estimation for multiple views using a proposed objective function that…

Computer Vision and Pattern Recognition · Computer Science 2016-07-29 Tanmay Gupta , Daeyun Shin , Naren Sivagnanadasan , Derek Hoiem

The last several years have seen significant progress in using depth cameras for tracking articulated objects such as human bodies, hands, and robotic manipulators. Most approaches focus on tracking skeletal parameters of a fixed shape…

Computer Vision and Pattern Recognition · Computer Science 2017-11-23 Aaron Walsman , Weilin Wan , Tanner Schmidt , Dieter Fox

Reconstructing 3D object models is playing an important role in many applications in the field of computer vision. Instead of employing a collection of cameras and/or sensors as in many studies, this paper proposes a simple way to build a…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Trong Nguyen Nguyen , Huu Hung Huynh , Jean Meunier

The availability of affordable and portable depth sensors has made scanning objects and people simpler than ever. However, dealing with occlusions and missing parts is still a significant challenge. The problem of reconstructing a (possibly…

Computer Vision and Pattern Recognition · Computer Science 2018-04-05 Or Litany , Alex Bronstein , Michael Bronstein , Ameesh Makadia

Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Jan Bednařík , Pascal Fua , Mathieu Salzmann

This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving. Based on a parametric body model, we present a robust processing pipeline achieving 3D…

Computer Vision and Pattern Recognition · Computer Science 2018-04-17 Thiemo Alldieck , Marcus Magnor , Weipeng Xu , Christian Theobalt , Gerard Pons-Moll

Much progress has been made in the supervised learning of 3D reconstruction of rigid objects from multi-view images or a video. However, it is more challenging to reconstruct severely deformed objects from a single-view RGB image in an…

Computer Vision and Pattern Recognition · Computer Science 2022-01-25 Jie Mei , Jingxi Yu , Suzanne Romain , Craig Rose , Kelsey Magrane , Graeme LeeSon , Jenq-Neng Hwang

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

Computer Vision and Pattern Recognition · Computer Science 2019-05-14 Hao Zhu , Xinxin Zuo , Sen Wang , Xun Cao , Ruigang Yang

This paper propose a interactive 3D modeling method and corresponding system based on single or multiple uncalibrated images. The main feature of this method is that, according to the modeling habits of ordinary people, the 3D model of the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhi He , Rui Wang , Wei Hua , Yuchi Huo

In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This paper proposes an innovative Simultaneous Localization and Mapping (SLAM) algorithm for…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Jingwei Song , Jun Wang , Liang Zhao , Shoudong Huang , Gamini Dissanayake

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

We propose a method for constructing generative models of 3D objects from a single 3D mesh. Our method produces a 3D morphable model that represents shape and albedo in terms of Gaussian processes. We define the shape deformations in…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Skylar Sutherland , Bernhard Egger , Joshua Tenenbaum

Most recent garment capturing techniques rely on acquiring multiple views of clothing, which may not always be readily available, especially in the case of pre-existing photographs from the web. As an alternative, we pro- pose a method that…

Computer Vision and Pattern Recognition · Computer Science 2016-09-13 Shan Yang , Tanya Ambert , Zherong Pan , Ke Wang , Licheng Yu , Tamara Berg , Ming C. Lin

This research proposes a novel adjustable algorithm for reconstructing 3D body shapes from front and side silhouettes. Most recent silhouette-based approaches use a deep neural network trained by silhouettes and key points to estimate the…

Computer Vision and Pattern Recognition · Computer Science 2023-01-03 Aref Hemati , Azam Bastanfard

We reconstruct 3D deformable object through time, in the context of a live pottery making process where the crafter molds the object. Because the object suffers from heavy hand interaction, and is being deformed, classical techniques cannot…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Raoul de Charette , Sotiris Manitsaris

We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image. While previous approaches address the deblurring problem only in the 2D image domain, our proposed…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Marc Pollefeys

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

Scene reconstruction from multi-view images is a fundamental problem in computer vision and graphics. Recent neural implicit surface reconstruction methods have achieved high-quality results; however, editing and manipulating the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Xiaoyang Lyu , Chirui Chang , Peng Dai , Yang-Tian Sun , Xiaojuan Qi

We present an approach to robustly track the geometry of an object that deforms over time from a set of input point clouds captured from a single viewpoint. The deformations we consider are caused by applying forces to known locations on…

Computer Vision and Pattern Recognition · Computer Science 2015-03-31 Stefanie Wuhrer , Jochen Lang , Motahareh Tekieh , Chang Shu

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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