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Creating realistic 3D animation remains a time-consuming and expertise-dependent process, requiring manual rigging, keyframing, and fine-tuning of complex motions. Meanwhile, video diffusion models have recently demonstrated remarkable…

Graphics · Computer Science 2025-12-17 Tianyi Xie , Yunuo Chen , Yaowei Guo , Yin Yang , Bolei Zhou , Demetri Terzopoulos , Ying Jiang , Chenfanfu Jiang

Reconstructing human dynamic vision from brain activity is a challenging task with great scientific significance. Although prior video reconstruction methods have made substantial progress, they still suffer from several limitations,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Yizhuo Lu , Changde Du , Chong Wang , Xuanliu Zhu , Liuyun Jiang , Xujin Li , Huiguang He

We consider the problem of estimating frame-level full human body meshes given a video of a person with natural motion dynamics. While much progress in this field has been in single image-based mesh estimation, there has been a recent…

Computer Vision and Pattern Recognition · Computer Science 2021-07-28 Runze Li , Srikrishna Karanam , Ren Li , Terrence Chen , Bir Bhanu , Ziyan Wu

3D human pose estimation from a monocular video has recently seen significant improvements. However, most state-of-the-art methods are kinematics-based, which are prone to physically implausible motions with pronounced artifacts. Current…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Jiefeng Li , Siyuan Bian , Chao Xu , Gang Liu , Gang Yu , Cewu Lu

Despite tremendous recent progress in human video generation, generative video diffusion models still struggle to capture the dynamics and physics of human motions faithfully. In this paper, we propose a new framework for human video…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Tao Hu , Varun Jampani

This paper studies full-body 3D human motion recovery from head-mounted device signals. Existing diffusion-based methods often rely on global distribution matching, leading to local joint reconstruction errors. We propose MotionGRPO, a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Nanjie Yao , Junlong Ren , Wenhao Shen , Hao Wang

We address the problem of generating realistic 3D motions of humans interacting with objects in a scene. Our key idea is to create a neural interaction field attached to a specific object, which outputs the distance to the valid interaction…

Computer Vision and Pattern Recognition · Computer Science 2023-07-17 Nilesh Kulkarni , Davis Rempe , Kyle Genova , Abhijit Kundu , Justin Johnson , David Fouhey , Leonidas Guibas

The reconstruction of three-dimensional dynamic scenes is a well-established yet challenging task within the domain of computer vision. In this paper, we propose a novel approach that combines the domains of 3D geometry reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 David Stotko , Reinhard Klein

While existing methods for reconstructing hand-object interactions have made impressive progress, they either focus on rigid or part-wise rigid objects-limiting their ability to model real-world objects (e.g., cloth, stuffed animals) that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Jihyun Lee , Changmin Lee , Donghwan Kim , Tae-Kyun Kim

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

Synthesizing realistic human-object interaction motions is a critical problem in VR/AR and human animation. Unlike the commonly studied scenarios involving a single human or hand interacting with one object, we address a more generic…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Wenkun He , Yun Liu , Ruitao Liu , Li Yi

In this paper we present a high fidelity and articulated 3D human foot model. The model is parameterised by a disentangled latent code in terms of shape, texture and articulated pose. While high fidelity models are typically created with…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Oliver Boyne , James Charles , Roberto Cipolla

Recently, regression-based methods have dominated the field of 3D human pose and shape estimation. Despite their promising results, a common issue is the misalignment between predictions and image observations, often caused by minor joint…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Tom Wehrbein , Bodo Rosenhahn , Iain Matthews , Carsten Stoll

We present a novel animatable 3D Gaussian model for rendering high-fidelity free-view human motions in real time. Compared to existing NeRF-based methods, the model owns better capability in synthesizing high-frequency details without the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Keyang Ye , Tianjia Shao , Kun Zhou

Incorporating temporal information effectively is important for accurate 3D human motion estimation and generation which have wide applications from human-computer interaction to AR/VR. In this paper, we present MoManifold, a novel human…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Ziqiang Dang , Tianxing Fan , Boming Zhao , Xujie Shen , Lei Wang , Guofeng Zhang , Zhaopeng Cui

We propose SDFDiff, a novel approach for image-based shape optimization using differentiable rendering of 3D shapes represented by signed distance functions (SDFs). Compared to other representations, SDFs have the advantage that they can…

Computer Vision and Pattern Recognition · Computer Science 2022-02-23 Yue Jiang , Dantong Ji , Zhizhong Han , Matthias Zwicker

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

Dynamic 3D interaction has been attracting a lot of attention recently. However, creating such 4D content remains challenging. One solution is to animate 3D scenes with physics-based simulation, which requires manually assigning precise…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Tianyu Huang , Haoze Zhang , Yihan Zeng , Zhilu Zhang , Hui Li , Wangmeng Zuo , Rynson W. H. Lau

In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and customizing their behaviors. However, current 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Fangfu Liu , Hanyang Wang , Shunyu Yao , Shengjun Zhang , Jie Zhou , Yueqi Duan

We introduce a novel task of reconstructing a time series of second-person 3D human body meshes from monocular egocentric videos. The unique viewpoint and rapid embodied camera motion of egocentric videos raise additional technical barriers…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Miao Liu , Dexin Yang , Yan Zhang , Zhaopeng Cui , James M. Rehg , Siyu Tang
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