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We present a novel framework for animating humans in 3D scenes using 3D Gaussian Splatting (3DGS), a neural scene representation that has recently achieved state-of-the-art photorealistic results for novel-view synthesis but remains…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Aymen Mir , Jian Wang , Riza Alp Guler , Chuan Guo , Gerard Pons-Moll , Bing Zhou

Implicit Neural Representations (INRs) employ neural networks to approximate discrete data as continuous functions. In the context of video data, such models can be utilized to transform the coordinates of pixel locations along with frame…

Computer Vision and Pattern Recognition · Computer Science 2026-02-19 Weronika Smolak-Dyżewska , Dawid Malarz , Kornel Howil , Jan Kaczmarczyk , Marcin Mazur , Przemysław Spurek

We present HAHA - a novel approach for animatable human avatar generation from monocular input videos. The proposed method relies on learning the trade-off between the use of Gaussian splatting and a textured mesh for efficient and high…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 David Svitov , Pietro Morerio , Lourdes Agapito , Alessio Del Bue

Motivation: Quickly obtaining high-quality MRI from accelerated acquisitions is important to mitigate motion artifacts, maintain patient comfort, and improve clinical efficiency. Goals: To obtain high-quality dynamic MRI using efficient,…

Medical Physics · Physics 2026-03-24 M. L. Terpstra , C. A. T. van den Berg

2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-agnostic or spatio-temporal feature overlapping embeddings to predict canonical Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Jierun Lin , Jiacong Chen , Qingyu Mao , Shuai Liu , Xiandong Meng , Fanyang Meng , Yongsheng Liang

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Jinfeng Liu , Lingtong Kong , Mi Zhou , Jinwen Chen , Dan Xu

Gaussian splatting has emerged as a powerful tool for high-fidelity reconstruction of dynamic scenes. However, existing methods primarily rely on implicit motion representations, such as encoding motions into neural networks or per-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xinyu Zhang , Haonan Chang , Yuhan Liu , Abdeslam Boularias

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

Reconstructing a dynamic target moving over a large area is challenging. Standard approaches for dynamic object reconstruction require dense coverage in both the viewing space and the temporal dimension, typically relying on multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Jun-Jee Chao , Volkan Isler

Articulated objects are common in the real world, yet modeling their structure and motion remains a challenging task for 3D reconstruction methods. In this work, we introduce Part$^{2}$GS, a novel framework for modeling articulated digital…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Tianjiao Yu , Vedant Shah , Muntasir Wahed , Ying Shen , Kiet A. Nguyen , Ismini Lourentzou

Recent 4D reconstruction methods have yielded impressive results but rely on sharp videos as supervision. However, motion blur often occurs in videos due to camera shake and object movement, while existing methods render blurry results when…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Renlong Wu , Zhilu Zhang , Mingyang Chen , Zifei Yan , Wangmeng Zuo

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

Monocular 3D shape recovery is fundamental to geometric understanding, yet achieving robust generalization across arbitrary viewpoints and unseen object categories remains a significant challenge. In this paper, we present a generalizable…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Yiyao Ma , Kai Chen , Zhongxiang Zhou , Zhuheng Song , Dongsheng Xie , Zelong Tan , Rong Xiong , Qi Dou

3D Gaussian Splatting has emerged as a powerful paradigm for explicit 3D scene representation, yet achieving efficient and consistent 3D segmentation remains challenging. Existing segmentation approaches typically rely on high-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Wentao Sun , Quanyun Wu , Hanqing Xu , Kyle Gao , Zhengsen Xu , Yiping Chen , Dedong Zhang , Lingfei Ma , John S. Zelek , Jonathan Li

Animating an object in 3D often requires an articulated structure, e.g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movements and surface deformations. However, existing models that…

Computer Vision and Pattern Recognition · Computer Science 2023-04-17 Tianshu Kuai , Akash Karthikeyan , Yash Kant , Ashkan Mirzaei , Igor Gilitschenski

Articulated objects are ubiquitous in daily life. Our goal is to achieve a high-quality reconstruction, segmentation of independent moving parts, and analysis of articulation. Recent methods analyse two different articulation states and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Hao Ai , Wenjie Chang , Jianbo Jiao , Ales Leonardis , Ofek Eyal

Recent advancements in neural rendering techniques have significantly enhanced the fidelity of 3D reconstruction. Notably, the emergence of 3D Gaussian Splatting (3DGS) has marked a significant milestone by adopting a discrete scene…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Licheng Shen , Ho Ngai Chow , Lingyun Wang , Tong Zhang , Mengqiu Wang , Yuxing Han

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

Existing full-body Gaussian avatar methods primarily optimize global reconstruction quality and often fail to preserve fine-grained facial geometry and expression details. This challenge arises from limited facial representational capacity…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Willem Menu , Erkut Akdag , Pedro Quesado , Yasaman Kashefbahrami , Egor Bondarev
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