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Related papers: Ani3DHuman: Photorealistic 3D Human Animation with…

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We present a new trainable system for physically plausible markerless 3D human motion capture, which achieves state-of-the-art results in a broad range of challenging scenarios. Unlike most neural methods for human motion capture, our…

Computer Vision and Pattern Recognition · Computer Science 2021-05-04 Soshi Shimada , Vladislav Golyanik , Weipeng Xu , Patrick Pérez , Christian Theobalt

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

In this paper, we introduce GaussianMotion, a novel human rendering model that generates fully animatable scenes aligned with textual descriptions using Gaussian Splatting. Although existing methods achieve reasonable text-to-3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Gyumin Shim , Sangmin Lee , Jaegul Choo

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility. The proposed approach leverages an implicit function representation of 3D human heads,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Yushi Lan , Feitong Tan , Di Qiu , Qiangeng Xu , Kyle Genova , Zeng Huang , Sean Fanello , Rohit Pandey , Thomas Funkhouser , Chen Change Loy , Yinda Zhang

Existing methods for human motion control in video generation typically rely on either 2D poses or explicit 3D parametric models (e.g., SMPL) as control signals. However, 2D poses rigidly bind motion to the driving viewpoint, precluding…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Zhixue Fang , Xu He , Songlin Tang , Haoxian Zhang , Qingfeng Li , Xiaoqiang Liu , Pengfei Wan , Kun Gai

The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely on high-quality, sharp images as input, which are often impractical to obtain in real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Muyao Niu , Yifan Zhan , Qingtian Zhu , Zhuoxiao Li , Wei Wang , Zhihang Zhong , Xiao Sun , Yinqiang Zheng

We introduce a method to synthesize animator guided human motion across 3D scenes. Given a set of sparse (3 or 4) joint locations (such as the location of a person's hand and two feet) and a seed motion sequence in a 3D scene, our method…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Aymen Mir , Xavier Puig , Angjoo Kanazawa , Gerard Pons-Moll

The estimation of 3D human motion from video has progressed rapidly but current methods still have several key limitations. First, most methods estimate the human in camera coordinates. Second, prior work on estimating humans in global…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Soyong Shin , Juyong Kim , Eni Halilaj , Michael J. Black

Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long runtime, or their limited quality. We introduce ActionMesh,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Remy Sabathier , David Novotny , Niloy J. Mitra , Tom Monnier

Traditionally, creating photo-realistic 3D head avatars requires a studio-level multi-view capture setup and expensive optimization during test-time, limiting the use of digital human doubles to the VFX industry or offline renderings. To…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Tobias Kirschstein , Javier Romero , Artem Sevastopolsky , Matthias Nießner , Shunsuke Saito

In this paper, we propose a novel approach to reconstruct 3D human body shapes based on a sparse set of RGBD frames using a single RGBD camera. We specifically focus on the realistic settings where human subjects move freely during the…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Xinxin Zuo , Sen Wang , Jiangbin Zheng , Weiwei Yu , Minglun Gong , Ruigang Yang , Li Cheng

In this paper, we present WonderHuman to reconstruct dynamic human avatars from a monocular video for high-fidelity novel view synthesis. Previous dynamic human avatar reconstruction methods typically require the input video to have full…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Zilong Wang , Zhiyang Dou , Yuan Liu , Cheng Lin , Xiao Dong , Yunhui Guo , Chenxu Zhang , Xin Li , Wenping Wang , Xiaohu Guo

Recent advances in 3D scene reconstruction and 4D human animation have broadened adoption, but integrating the two remains difficult. Key challenges include placing humans at plausible locations and scales without interpenetration, aligning…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Qingyang Liu , Bingjie Gao , Weiheng Huang , Jun Zhang , Zhongqian Sun , Yang Wei , Fengrui Liu , Zelin Peng , Qianli Ma , Shuai Yang , Zhaohe Liao , Haonan Zhao , Li Niu

Recent years have witnessed tremendous progress in the 3D reconstruction of dynamic humans from a monocular video with the advent of neural rendering techniques. This task has a wide range of applications, including the creation of virtual…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Kanghao Chen , Zeyu Wang , Lin Wang

Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation. Recent score-based generative models (SGMs) have demonstrated impressive results on this task. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Yu Hua , Weiming Liu , Gui Xu , Yaqing Hou , Yew-Soon Ong , Qiang Zhang

We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner. Existing approaches rely on training sequences that contain captured human…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Kaifeng Zhao , Yan Zhang , Shaofei Wang , Thabo Beeler , Siyu Tang

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

Personalized 3D avatars require an animatable representation of digital humans. Doing so instantly from monocular videos offers scalability to broad class of users and wide-scale applications. In this paper, we present a fast, simple, yet…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Pramish Paudel , Anubhav Khanal , Ajad Chhatkuli , Danda Pani Paudel , Jyoti Tandukar

As humans, we aspire to create media content that is both freely willed and readily controlled. Thanks to the prominent development of generative techniques, we now can easily utilize 2D diffusion methods to synthesize images controlled by…

Graphics · Computer Science 2024-05-15 Wenqi Dong , Bangbang Yang , Lin Ma , Xiao Liu , Liyuan Cui , Hujun Bao , Yuewen Ma , Zhaopeng Cui
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