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Related papers: MonoPerfCap: Human Performance Capture from Monocu…

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We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage…

Computer Vision and Pattern Recognition · Computer Science 2019-01-28 Marc Habermann , Weipeng Xu , Michael Zollhoefer , Gerard Pons-Moll , Christian Theobalt

Capturing the dynamically deforming 3D shape of clothed human is essential for numerous applications, including VR/AR, autonomous driving, and human-computer interaction. Existing methods either require a highly specialized capturing setup,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Chen Guo , Xu Chen , Jie Song , Otmar Hilliges

3D human motion capture from monocular RGB images respecting interactions of a subject with complex and possibly deformable environments is a very challenging, ill-posed and under-explored problem. Existing methods address it only weakly…

Computer Vision and Pattern Recognition · Computer Science 2022-08-18 Zhi Li , Soshi Shimada , Bernt Schiele , Christian Theobalt , Vladislav Golyanik

Monocular 3D human performance capture is indispensable for many applications in computer graphics and vision for enabling immersive experiences. However, detailed capture of humans requires tracking of multiple aspects, including the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-12 Yue Jiang , Marc Habermann , Vladislav Golyanik , Christian Theobalt

Human performance capture is a highly important computer vision problem with many applications in movie production and virtual/augmented reality. Many previous performance capture approaches either required expensive multi-view setups or…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Marc Habermann , Weipeng Xu , Michael Zollhoefer , Gerard Pons-Moll , Christian Theobalt

Human performance capture is a highly important computer vision problem with many applications in movie production and virtual/augmented reality. Many previous performance capture approaches either required expensive multi-view setups or…

Computer Vision and Pattern Recognition · Computer Science 2020-03-19 Marc Habermann , Weipeng Xu , Michael Zollhoefer , Gerard Pons-Moll , Christian Theobalt

Recovering 3D full-body human pose is a challenging problem with many applications. It has been successfully addressed by motion capture systems with body worn markers and multiple cameras. In this paper, we address the more challenging…

Computer Vision and Pattern Recognition · Computer Science 2018-03-12 Xiaowei Zhou , Menglong Zhu , Georgios Pavlakos , Spyridon Leonardos , Kostantinos G. Derpanis , Kostas Daniilidis

Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-occlusion, especially for the monocular setting. In this…

Computer Vision and Pattern Recognition · Computer Science 2021-07-19 Xin Chen , Anqi Pang , Wei Yang , Yuexin Ma , Lan Xu , Jingyi Yu

We present the first approach to volumetric performance capture and novel-view rendering at real-time speed from monocular video, eliminating the need for expensive multi-view systems or cumbersome pre-acquisition of a personalized template…

Computer Vision and Pattern Recognition · Computer Science 2020-07-29 Ruilong Li , Yuliang Xiu , Shunsuke Saito , Zeng Huang , Kyle Olszewski , Hao Li

We introduce MulayCap, a novel human performance capture method using a monocular video camera without the need for pre-scanning. The method uses "multi-layer" representations for geometry reconstruction and texture rendering, respectively.…

Computer Vision and Pattern Recognition · Computer Science 2020-10-05 Zhaoqi Su , Weilin Wan , Tao Yu , Lingjie Liu , Lu Fang , Wenping Wang , Yebin Liu

We present a method to reconstruct time-consistent human body models from monocular videos, focusing on extremely loose clothing or handheld object interactions. Prior work in human reconstruction is either limited to tight clothing with no…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Jeff Tan , Donglai Xiang , Shubham Tulsiani , Deva Ramanan , Gengshan Yang

Recovering temporally consistent 3D human body pose, shape and motion from a monocular video is a challenging task due to (self-)occlusions, poor lighting conditions, complex articulated body poses, depth ambiguity, and limited availability…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Sushovan Chanda , Amogh Tiwari , Lokender Tiwari , Brojeshwar Bhowmick , Avinash Sharma , Hrishav Barua

Recent advances in image-based human pose estimation make it possible to capture 3D human motion from a single RGB video. However, the inherent depth ambiguity and self-occlusion in a single view prohibit the recovery of as high-quality…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Junting Dong , Qing Shuai , Yuanqing Zhang , Xian Liu , Xiaowei Zhou , Hujun Bao

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Human motion recovery for real-world interaction demands both precise action details and metric-scale trajectories. Recovering absolute human pose from monocular input presents a viable solution, but faces two main challenges: (1) models'…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhumei Wang , Zechen Hu , Ruoxi Guo , Huaijin Pi , Ziyong Feng , Liang Zhang , Mingtao Pei , Siyuan Huang

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

We present a novel method to learn temporally consistent 3D reconstruction of clothed people from a monocular video. Recent methods for 3D human reconstruction from monocular video using volumetric, implicit or parametric human shape…

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

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack of temporally consistent handling of plausible clothing…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Moritz Kappel , Vladislav Golyanik , Mohamed Elgharib , Jann-Ole Henningson , Hans-Peter Seidel , Susana Castillo , Christian Theobalt , Marcus Magnor

We present a method to capture temporally coherent dynamic clothing deformation from a monocular RGB video input. In contrast to the existing literature, our method does not require a pre-scanned personalized mesh template, and thus can be…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Donglai Xiang , Fabian Prada , Chenglei Wu , Jessica Hodgins

We present the first method to capture the 3D total motion of a target person from a monocular view input. Given an image or a monocular video, our method reconstructs the motion from body, face, and fingers represented by a 3D deformable…

Computer Vision and Pattern Recognition · Computer Science 2018-12-05 Donglai Xiang , Hanbyul Joo , Yaser Sheikh
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