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Related papers: Rig3DGS: Creating Controllable Portraits from Casu…

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This paper considers the problem of modeling articulated objects captured in 2D videos to enable novel view synthesis, while also being easily editable, drivable, and re-posable. To tackle this challenging problem, we propose RigGS, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yuxin Yao , Zhi Deng , Junhui Hou

Reconstructing dynamic 3D scenes from monocular videos is a fundamental yet highly challenging task, as real-world motions often involve both long-term smooth transformations and short-term complex deformations. Existing methods either…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Chenyu Wu , Wanhua Li , Zhu-Tian Chen , Hanspeter Pfister

4D reconstruction from casually captured monocular videos is challenging due to inherent ambiguity in reconstructing dynamic 3D geometry. To address this challenge, we introduce Robust Dynamic Gaussian Splatting (RoDyGS), a method that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Junmyeong Lee , Hoseung Choi , Yoonwoo Jeong , Minsu Cho

Volumetric neural rendering methods, such as neural radiance fields (NeRFs), have enabled photo-realistic novel view synthesis. However, in their standard form, NeRFs do not support the editing of objects, such as a human head, within a…

Computer Vision and Pattern Recognition · Computer Science 2022-06-15 ShahRukh Athar , Zexiang Xu , Kalyan Sunkavalli , Eli Shechtman , Zhixin Shu

Creating a photorealistic scene and human reconstruction from a single monocular in-the-wild video figures prominently in the perception of a human-centric 3D world. Recent neural rendering advances have enabled holistic human-scene…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Zetong Zhang , Manuel Kaufmann , Lixin Xue , Jie Song , Martin R. Oswald

Real-time rendering of human head avatars is a cornerstone of many computer graphics applications, such as augmented reality, video games, and films, to name a few. Recent approaches address this challenge with computationally efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Kartik Teotia , Hyeongwoo Kim , Pablo Garrido , Marc Habermann , Mohamed Elgharib , Christian Theobalt

Recent advancements in 3D Gaussian Splatting (3DGS) have unlocked significant potential for modeling 3D head avatars, providing greater flexibility than mesh-based methods and more efficient rendering compared to NeRF-based approaches.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Peizhi Yan , Rabab Ward , Qiang Tang , Shan Du

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

Animatable 3D reconstruction has significant applications across various fields, primarily relying on artists' handcraft creation. Recently, some studies have successfully constructed animatable 3D models from monocular videos. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Tingyang Zhang , Qingzhe Gao , Weiyu Li , Libin Liu , Baoquan Chen

We introduce an approach that creates animatable human avatars from monocular videos using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields (NeRFs) achieve high-quality novel-view/novel-pose image synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Zhiyin Qian , Shaofei Wang , Marko Mihajlovic , Andreas Geiger , Siyu Tang

3D Gaussian Splatting (3DGS) has gained significant attention for their high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Sangyoun Lee

In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocular dynamic NeRF or Gaussian Splatting methods strongly rely on the rapid move ment of input…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Qingming Liu , Yuan Liu , Jiepeng Wang , Xianqiang Lyv , Peng Wang , Wenping Wang , Junhui Hou

High-fidelity reconstruction of 3D human avatars has a wild application in visual reality. In this paper, we introduce FAGhead, a method that enables fully controllable human portraits from monocular videos. We explicit the traditional 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Yixin Xuan , Xinyang Li , Gongxin Yao , Shiwei Zhou , Donghui Sun , Xiaoxin Chen , Yu Pan

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking heads. However, achieving precise control over fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Shaoyang Xie , Xiaofeng Cong , Baosheng Yu , Zhipeng Gui , Jie Gui , Yuan Yan Tang , James Tin-Yau Kwok

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

3D Gaussian Splatting (3DGS) has emerged as a powerful representation due to its efficiency and high-fidelity rendering. 3DGS training requires a known camera pose for each input view, typically obtained by Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Zhen-Hui Dong , Sheng Ye , Yu-Hui Wen , Nannan Li , Yong-Jin Liu

Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision and graphics. While existing 3D human avatar modeling approaches can effectively capture…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Yuze Su , Hongsong Wang , Jie Gui , Liang Wang

Previous animatable 3D-aware GANs for human generation have primarily focused on either the human head or full body. However, head-only videos are relatively uncommon in real life, and full body generation typically does not deal with…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yue Wu , Sicheng Xu , Jianfeng Xiang , Fangyun Wei , Qifeng Chen , Jiaolong Yang , Xin Tong

3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic scenes because 3D Gaussian parameters need to be updated per…

Graphics · Computer Science 2024-07-08 Kai Katsumata , Duc Minh Vo , Hideki Nakayama
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