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Related papers: Occluded Human Mesh Recovery

200 papers

3D Human Mesh Reconstruction (HMR) from 2D RGB images faces challenges in environments with poor lighting, privacy concerns, or occlusions. These weaknesses of RGB imaging can be complemented by acoustic signals, which are widely available,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xiaoxuan Liang , Wuyang Zhang , Hong Zhou , Zhaolong Wei , Sicheng Zhu , Yansong Li , Rui Yin , Jiantao Yuan , Jeremy Gummeson

Human mesh recovery from arbitrary multi-view images involves two characteristics: the arbitrary camera poses and arbitrary number of camera views. Because of the variability, designing a unified framework to tackle this task is…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Xiaoben Li , Mancheng Meng , Ziyan Wu , Terrence Chen , Fan Yang , Dinggang Shen

In this study, we focus on the problem of 3D human mesh recovery from a single image under obscured conditions. Most state-of-the-art methods aim to improve 2D alignment technologies, such as spatial averaging and 2D joint sampling.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Jiahao Li , Zongxin Yang , Xiaohan Wang , Jianxin Ma , Chang Zhou , Yi Yang

Although significant progress has been achieved on monocular maker-less human motion capture in recent years, it is still hard for state-of-the-art methods to obtain satisfactory results in occlusion scenarios. There are two main reasons:…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Buzhen Huang , Yuan Shu , Jingyi Ju , Yangang Wang

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

Human pose estimation aims at locating the specific joints of humans from the images or videos. While existing deep learning-based methods have achieved high positioning accuracy, they often struggle with generalization in occlusion…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Gangtao Han , Chunxiao Song , Song Wang , Hao Wang , Enqing Chen , Guanghui Wang

Conventional approaches to human mesh recovery predominantly employ a region-based strategy. This involves initially cropping out a human-centered region as a preprocessing step, with subsequent modeling focused on this zoomed-in image.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Zeyu Wang , Zhenzhen Weng , Serena Yeung-Levy

Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digital content creation, but remains challenging under frequent occlusions in real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Zhiyin Qian , Siwei Zhang , Bharat Lal Bhatnagar , Federica Bogo , Siyu Tang

Human pose and shape (HPS) estimation presents challenges in diverse scenarios such as crowded scenes, person-person interactions, and single-view reconstruction. Existing approaches lack mechanisms to incorporate auxiliary "side…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Yufu Wang , Yu Sun , Priyanka Patel , Kostas Daniilidis , Michael J. Black , Muhammed Kocabas

We describe Human Mesh Recovery (HMR), an end-to-end framework for reconstructing a full 3D mesh of a human body from a single RGB image. In contrast to most current methods that compute 2D or 3D joint locations, we produce a richer and…

Computer Vision and Pattern Recognition · Computer Science 2018-06-26 Angjoo Kanazawa , Michael J. Black , David W. Jacobs , Jitendra Malik

Multi-person human mesh recovery from a single image is a challenging task, hindered by the scarcity of in-the-wild training data. Prevailing in-the-wild human mesh pseudo-ground-truth (pGT) generation pipelines are single-person-centric,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Kaiwen Wang , Kaili Zheng , Yiming Shi , Chenyi Guo , Ji Wu

Single-image human mesh recovery provides a compact 3D, person-centric representation that supports analysis, animation, AR and VR, rehabilitation, and human-computer interaction. However, prevailing systems impose an intact-limb prior and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Jiaying Ying , Heming Du , Kaihao Zhang , Sean M. Tweedy , Xin Yu

In this paper, we tackle the problem of human de-occlusion which reasons about occluded segmentation masks and invisible appearance content of humans. In particular, a two-stage framework is proposed to estimate the invisible portions and…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Qiang Zhou , Shiyin Wang , Yitong Wang , Zilong Huang , Xinggang Wang

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

We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions and tracks human bodies even when they go outside the camera's field of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-31 Ye Yuan , Umar Iqbal , Pavlo Molchanov , Kris Kitani , Jan Kautz

We consider the problem of obese human mesh recovery, i.e., fitting a parametric human mesh to images of obese people. Despite obese person mesh fitting being an important problem with numerous applications (e.g., healthcare), much recent…

Computer Vision and Pattern Recognition · Computer Science 2021-07-14 Ren Li , Meng Zheng , Srikrishna Karanam , Terrence Chen , Ziyan Wu

Advances in Deep Learning have recently made it possible to recover full 3D meshes of human poses from individual images. However, extension of this notion to videos for recovering temporally coherent poses still remains unexplored. A major…

Computer Vision and Pattern Recognition · Computer Science 2019-07-02 Jian Liu , Naveed Akhtar , Ajmal Mian

Making top-down human pose estimation method present both good performance and high efficiency is appealing. Mask RCNN can largely improve the efficiency by conducting person detection and pose estimation in a single framework, as the…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Ling Li , Lin Zhao , Linhao Xu , Jie Xu

With 3D data rapidly emerging as an important form of multimedia information, 3D human mesh recovery technology has also advanced accordingly. However, current methods mainly focus on handling humans wearing tight clothing and perform…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yunqi Gao , Leyuan Liu , Yuhan Li , Changxin Gao , Yuanyuan Liu , Jingying Chen

We describe an end-to-end method for recovering 3D human body mesh from single images and monocular videos. Different from the existing methods try to obtain all the complex 3D pose, shape, and camera parameters from one coupling feature,…

Computer Vision and Pattern Recognition · Computer Science 2019-09-18 Sun Yu , Ye Yun , Liu Wu , Gao Wenpeng , Fu YiLi , Mei Tao