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We consider the problem of estimating a parametric model of 3D human mesh from a single image. While there has been substantial recent progress in this area with direct regression of model parameters, these methods only implicitly exploit…

Computer Vision and Pattern Recognition · Computer Science 2020-07-15 Georgios Georgakis , Ren Li , Srikrishna Karanam , Terrence Chen , Jana Kosecka , Ziyan Wu

Reconstructing 3D clothed humans from images is fundamental to applications like virtual try-on, avatar creation, and mixed reality. While recent advances have enhanced human body recovery, accurate reconstruction of garment geometry --…

Graphics · Computer Science 2025-05-16 Ren Li , Cong Cao , Corentin Dumery , Yingxuan You , Hao Li , Pascal Fua

Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image alignment due to the lack of explicit 2D-3D correspondences. In…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Chongyang Xu , Buzhen Huang , Chengfang Zhang , Ziliang Feng , Yangang Wang

Inverse rendering in a 3D format denoted to recovering the 3D properties of a scene given 2D input image(s) and is typically done using 3D Morphable Model (3DMM) based methods from single view images. These models formulate each face as a…

Computer Vision and Pattern Recognition · Computer Science 2017-09-01 Shima Kamyab , Ali Ghodsi , S. Zohreh Azimifar

We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment. To achieve this, we design a 2D representation called UV position map which records the 3D shape of a complete face…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Yao Feng , Fan Wu , Xiaohu Shao , Yanfeng Wang , Xi Zhou

We study how to synthesize novel views of human body from a single image. Though recent deep learning based methods work well for rigid objects, they often fail on objects with large articulation, like human bodies. The core step of…

Computer Vision and Pattern Recognition · Computer Science 2018-04-13 Hao Zhu , Hao Su , Peng Wang , Xun Cao , Ruigang Yang

We present an end-to-end virtual try-on pipeline, that can fit different clothes on a personalized 3-D human model, reconstructed using a single RGB image. Our main idea is to construct an animatable 3-D human model and try-on different…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Gayal Kuruppu , Bumuthu Dilshan , Shehan Samarasinghe , Nipuna Madhushan , Ranga Rodrigo

Markerless motion capture algorithms require a 3D body with properly personalized skeleton dimension and/or body shape and appearance to successfully track a person. Unfortunately, many tracking methods consider model personalization a…

Computer Vision and Pattern Recognition · Computer Science 2016-10-24 Helge Rhodin , Nadia Robertini , Dan Casas , Christian Richardt , Hans-Peter Seidel , Christian Theobalt

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

Constructing and animating humans is an important component for building virtual worlds in a wide variety of applications such as virtual reality or robotics testing in simulation. As there are exponentially many variations of humans with…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Ze Yang , Shenlong Wang , Sivabalan Manivasagam , Zeng Huang , Wei-Chiu Ma , Xinchen Yan , Ersin Yumer , Raquel Urtasun

In this paper, we present an end-to-end learning framework for detailed 3D face reconstruction from a single image. Our approach uses a 3DMM-based coarse model and a displacement map in UV-space to represent a 3D face. Unlike previous work…

Computer Vision and Pattern Recognition · Computer Science 2020-09-03 Yajing Chen , Fanzi Wu , Zeyu Wang , Yibing Song , Yonggen Ling , Linchao Bao

We present THUNDR, a transformer-based deep neural network methodology to reconstruct the 3d pose and shape of people, given monocular RGB images. Key to our methodology is an intermediate 3d marker representation, where we aim to combine…

Computer Vision and Pattern Recognition · Computer Science 2021-06-18 Mihai Zanfir , Andrei Zanfir , Eduard Gabriel Bazavan , William T. Freeman , Rahul Sukthankar , Cristian Sminchisescu

The objective of this work is to infer the 3D shape of an object from a single image. We use sculptures as our training and test bed, as these have great variety in shape and appearance. To achieve this we build on the success of multiple…

Computer Vision and Pattern Recognition · Computer Science 2018-10-05 Olivia Wiles , Andrew Zisserman

3D reconstruction from 2D inputs, especially for non-rigid objects like humans, presents unique challenges due to the significant range of possible deformations. Traditional methods often struggle with non-rigid shapes, which require…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Fahd Alhamazani , Yu-Kun Lai , Paul L. Rosin

Reconstruction of the shape and motion of humans from RGB-D is a challenging problem, receiving much attention in recent years. Recent approaches for full-body reconstruction use a statistic shape model, which is built upon accurate…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Ryosuke Kimura , Akihiko Sayo , Fabian Lorenzo Dayrit , Yuta Nakashima , Hiroshi Kawasaki , Ambrosio Blanco , Katsushi Ikeuchi

Sketch-based modeling strives to bring the ease and immediacy of drawing to the 3D world. However, while drawings are easy for humans to create, they are very challenging for computers to interpret due to their sparsity and ambiguity. We…

Graphics · Computer Science 2018-06-20 Johanna Delanoy , Mathieu Aubry , Phillip Isola , Alexei A. Efros , Adrien Bousseau

In this paper, we address the problem of learning 3D human pose and body shape from 2D image dataset, without having to use 3D dataset (body shape and pose). The idea is to use dense correspondences between image points and a body surface,…

Computer Vision and Pattern Recognition · Computer Science 2019-07-30 Yusuke Yoshiyasu , Lucas Gamez

This paper introduces a novel pipeline to reconstruct the geometry of interacting multi-person in clothing on a globally coherent scene space from a single image. The main challenge arises from the occlusion: a part of a human body is not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Junuk Cha , Hansol Lee , Jaewon Kim , Nhat Nguyen Bao Truong , Jae Shin Yoon , Seungryul Baek

3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses. This is because the uncertainty of the estimated 2D landmarks will affect the quality of face reconstruction. In…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Kun Li , Jing Yang , Nianhong Jiao , Jinsong Zhang , Yu-Kun Lai

We propose a new approach for constructing a 3D representation from a 2D wireframe drawing. A drawing is simply a parallel projection of a 3D object onto a 2D surface; humans are able to recreate mental 3D models from 2D representations…

Computer Vision and Pattern Recognition · Computer Science 2010-07-16 Kyle Johnson , Clayton Chang , Hod Lipson