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Related papers: HumanRAM: Feed-forward Human Reconstruction and An…

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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

Existing Human NeRF methods for reconstructing 3D humans typically rely on multiple 2D images from multi-view cameras or monocular videos captured from fixed camera views. However, in real-world scenarios, human images are often captured…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Shoukang Hu , Fangzhou Hong , Liang Pan , Haiyi Mei , Lei Yang , Ziwei Liu

We introduce a free-viewpoint rendering method -- HumanNeRF -- that works on a given monocular video of a human performing complex body motions, e.g. a video from YouTube. Our method enables pausing the video at any frame and rendering the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-16 Chung-Yi Weng , Brian Curless , Pratul P. Srinivasan , Jonathan T. Barron , Ira Kemelmacher-Shlizerman

Single-image human reconstruction is vital for digital human modeling applications but remains an extremely challenging task. Current approaches rely on generative models to synthesize multi-view images for subsequent 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Boyuan Wang , Runqi Ouyang , Xiaofeng Wang , Zheng Zhu , Guosheng Zhao , Chaojun Ni , Xiaopei Zhang , Guan Huang , Yijie Ren , Lihong Liu , Xingang Wang

In this paper, we propose a dense monocular SLAM system, named DeepRelativeFusion, that is capable to recover a globally consistent 3D structure. To this end, we use a visual SLAM algorithm to reliably recover the camera poses and…

Computer Vision and Pattern Recognition · Computer Science 2021-07-13 Shing Yan Loo , Syamsiah Mashohor , Sai Hong Tang , Hong Zhang

We propose MeshLRM, a novel LRM-based approach that can reconstruct a high-quality mesh from merely four input images in less than one second. Different from previous large reconstruction models (LRMs) that focus on NeRF-based…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xinyue Wei , Kai Zhang , Sai Bi , Hao Tan , Fujun Luan , Valentin Deschaintre , Kalyan Sunkavalli , Hao Su , Zexiang Xu

RAM incorporates a motion-aware semantic tracker with adaptive Kalman filtering to achieve robust identity association under severe occlusions and dynamic interactions. A memory-augmented Temporal HMR module further enhances human motion…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Sen Jia , Ning Zhu , Jinqin Zhong , Jiale Zhou , Huaping Zhang , Jenq-Neng Hwang , Lei Li

Recent methods for dynamic human reconstruction have attained promising reconstruction results. Most of these methods rely only on RGB color supervision without considering explicit geometric constraints. This leads to existing human…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Junhui Yin , Wei Yin , Hao Chen , Xuqian Ren , Zhanyu Ma , Jun Guo , Yifan Liu

We have recently seen tremendous progress in the neural advances for photo-real human modeling and rendering. However, it's still challenging to integrate them into an existing mesh-based pipeline for downstream applications. In this paper,…

Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of information for understanding 3D humans, 3D scenes, and the interactions between them. In fact, we demonstrate…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Hongwei Yi , Chun-Hao P. Huang , Dimitrios Tzionas , Muhammed Kocabas , Mohamed Hassan , Siyu Tang , Justus Thies , Michael J. Black

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

Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits inefficiencies, subpar geometric and texture quality, as well…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Mengfei Li , Xiaoxiao Long , Yixun Liang , Weiyu Li , Yuan Liu , Peng Li , Wenhan Luo , Wenping Wang , Yike Guo

Demystifying complex human-ground interactions is essential for accurate and realistic 3D human motion reconstruction from RGB videos, as it ensures consistency between the humans and the ground plane. Prior methods have modeled…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Sihan Ma , Qiong Cao , Hongwei Yi , Jing Zhang , Dacheng Tao

Recent works on dynamic 3D neural field reconstruction assume the input from synchronized multi-view videos whose poses are known. The input constraints are often not satisfied in real-world setups, making the approach impractical. We show…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Changwoon Choi , Jeongjun Kim , Geonho Cha , Minkwan Kim , Dongyoon Wee , Young Min Kim

Current 3D human animation methods struggle to achieve photorealism: kinematics-based approaches lack non-rigid dynamics (e.g., clothing dynamics), while methods that leverage video diffusion priors can synthesize non-rigid motion but…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Qi Sun , Can Wang , Jiaxiang Shang , Yingchun Liu , Jing Liao

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

In the rapidly evolving landscape of digital content creation, the demand for fast, convenient, and autonomous methods of crafting detailed 3D reconstructions of humans has grown significantly. Addressing this pressing need, our AirNeRF…

Robotics · Computer Science 2024-07-16 Alexey Kotcov , Maria Dronova , Vladislav Cheremnykh , Sausar Karaf , Dzmitry Tsetserukou

Photo-real digital human avatars are of enormous importance in graphics, as they enable immersive communication over the globe, improve gaming and entertainment experiences, and can be particularly beneficial for AR and VR settings.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Marc Habermann , Lingjie Liu , Weipeng Xu , Gerard Pons-Moll , Michael Zollhoefer , Christian Theobalt

Recovering a dynamic 3D scene from a long monocular video is crucial for dense geometry, camera motion, and temporal correspondence to remain consistent in a shared coordinate system. Existing methods face two key challenges: (1)…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Chenyi Xu , Yihao Wu , Liqi Yan , Chao Yang , Jianhui Zhang , Fangli Guan , Pan Li

This paper presents a new system to obtain dense object reconstructions along with 6-DoF poses from a single image. Geared towards high fidelity reconstruction, several recent approaches leverage implicit surface representations and deep…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Aniket Pokale , Aditya Aggarwal , K. Madhava Krishna