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Most deep pose estimation methods need to be trained for specific object instances or categories. In this work we propose a completely generic deep pose estimation approach, which does not require the network to have been trained on…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Yang Xiao , Xuchong Qiu , Pierre-Alain Langlois , Mathieu Aubry , Renaud Marlet

In this paper, we present NeuralReshaper, a novel method for semantic reshaping of human bodies in single images using deep generative networks. To achieve globally coherent reshaping effects, our approach follows a fit-then-reshape…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Beijia Chen , Yuefan Shen , Hongbo Fu , Xiang Chen , Kun Zhou , Youyi Zheng

Monocular image-based 3D reconstruction of faces is a long-standing problem in computer vision. Since image data is a 2D projection of a 3D face, the resulting depth ambiguity makes the problem ill-posed. Most existing methods rely on…

Computer Vision and Pattern Recognition · Computer Science 2019-04-10 Ayush Tewari , Florian Bernard , Pablo Garrido , Gaurav Bharaj , Mohamed Elgharib , Hans-Peter Seidel , Patrick Pérez , Michael Zollhöfer , Christian Theobalt

In this paper, we define and study a new Cloth2Body problem which has a goal of generating 3D human body meshes from a 2D clothing image. Unlike the existing human mesh recovery problem, Cloth2Body needs to address new and emerging…

Computer Vision and Pattern Recognition · Computer Science 2023-09-29 Lu Dai , Liqian Ma , Shenhan Qian , Hao Liu , Ziwei Liu , Hui Xiong

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 \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

In this paper, we present a deep-learning based method for estimating the 3D structure of a bone from a pair of 2D X-ray images. Our triplet loss-trained neural network selects the most closely matching 3D bone shape from a predefined set…

Computer Vision and Pattern Recognition · Computer Science 2020-10-12 Jana Čavojská , Julian Petrasch , Nicolas J. Lehmann , Agnès Voisard , Peter Böttcher

We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view imagery. In contrast to previous work, our controllable 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-09-01 Marc Habermann , Lingjie Liu , Weipeng Xu , Michael Zollhoefer , Gerard Pons-Moll , Christian Theobalt

Deep networks trained on millions of facial images are believed to be closely approaching human-level performance in face recognition. However, open world face recognition still remains a challenge. Although, 3D face recognition has an…

Computer Vision and Pattern Recognition · Computer Science 2020-12-03 Syed Zulqarnain Gilani , Ajmal Mian

This paper presents a simple yet powerful method for 3D human mesh reconstruction from a single RGB image. Most recently, the non-local interactions of the whole mesh vertices have been effectively estimated in the transformer while the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Jeonghwan Kim , Mi-Gyeong Gwon , Hyunwoo Park , Hyukmin Kwon , Gi-Mun Um , Wonjun Kim

We propose a deep learning approach for finding dense correspondences between 3D scans of people. Our method requires only partial geometric information in the form of two depth maps or partial reconstructed surfaces, works for humans in…

Computer Vision and Pattern Recognition · Computer Science 2016-06-28 Lingyu Wei , Qixing Huang , Duygu Ceylan , Etienne Vouga , Hao Li

3D human shape and pose estimation from monocular images has been an active area of research in computer vision, having a substantial impact on the development of new applications, from activity recognition to creating virtual avatars.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Xiangyu Xu , Hao Chen , Francesc Moreno-Noguer , Laszlo A. Jeni , Fernando De la Torre

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface as a unified representation for 3D reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Xinyi Yu , Liqin Lu , Jintao Rong , Guangkai Xu , Linlin Ou

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

Recovering the 3D shape of a person from its 2D appearance is ill-posed due to ambiguities. Nevertheless, with the help of convolutional neural networks (CNN) and prior knowledge on the 3D human body, it is possible to overcome such…

Computer Vision and Pattern Recognition · Computer Science 2020-04-23 Hayato Onizuka , Zehra Hayirci , Diego Thomas , Akihiro Sugimoto , Hideaki Uchiyama , Rin-ichiro Taniguchi

In this work, we present an automated workflow to bring human figures, one of the most frequently appearing entities on pictorial maps, to the third dimension. Our workflow is based on training data and neural networks for single-view 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-06-28 Raimund Schnürer , A. Cengiz Öztireli , Magnus Heitzler , René Sieber , Lorenz Hurni

In this paper, we propose the first sketching system for interactively personalized and photorealistic face caricaturing. Input an image of a human face, the users can create caricature photos by manipulating its facial feature curves. Our…

Computer Vision and Pattern Recognition · Computer Science 2018-07-25 Xiaoguang Han , Kangcheng Hou , Dong Du , Yuda Qiu , Yizhou Yu , Kun Zhou , Shuguang Cui

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

The availability of affordable 3D full body reconstruction systems has given rise to free-viewpoint video (FVV) of human shapes. Most existing solutions produce temporally uncorrelated point clouds or meshes with unknown point/vertex…

Computer Vision and Pattern Recognition · Computer Science 2018-10-15 Zhong Li , Minye Wu , Wangyiteng Zhou , Jingyi Yu

With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step…

Computer Vision and Pattern Recognition · Computer Science 2017-04-25 Shu Zhang , Hui Yu , Ting Wang , Junyu Dong , Honghai Liu
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