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Many works have succeeded in reconstructing Gaussian human avatars from multi-view videos. However, they either struggle to capture pose-dependent appearance details with a single MLP, or rely on a computationally intensive neural network…

Graphics · Computer Science 2025-04-29 Youyi Zhan , Tianjia Shao , Yin Yang , Kun Zhou

Implicit neural representations (INRs) recently achieved great success in image representation and compression, offering high visual quality and fast rendering speeds with 10-1000 FPS, assuming sufficient GPU resources are available.…

Image and Video Processing · Electrical Eng. & Systems 2024-07-10 Xinjie Zhang , Xingtong Ge , Tongda Xu , Dailan He , Yan Wang , Hongwei Qin , Guo Lu , Jing Geng , Jun Zhang

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

Video tokenization procedure is critical for a wide range of video processing tasks. Most existing approaches directly transform video into fixed-grid and patch-wise tokens, which exhibit limited versatility. Spatially, uniformly allocating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Zhenghao Chen , Zicong Chen , Lei Liu , Yiming Wu , Dong Xu

Reconstructing dynamic 3D scenes from monocular videos remains a fundamental challenge in 3D vision. While 3D Gaussian Splatting (3DGS) achieves real-time rendering in static settings, extending it to dynamic scenes is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Jianing Chen , Zehao Li , Yujun Cai , Hao Jiang , Chengxuan Qian , Juyuan Kang , Shuqin Gao , Honglong Zhao , Tianlu Mao , Yucheng Zhang

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Creating and customizing a 3D clothed avatar from textual descriptions is a critical and challenging task. Traditional methods often treat the human body and clothing as inseparable, limiting users' ability to freely mix and match garments.…

Graphics · Computer Science 2025-03-18 Jia Gong , Shenyu Ji , Lin Geng Foo , Kang Chen , Hossein Rahmani , Jun Liu

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

Dynamic 4D Gaussian Splatting (4DGS) effectively extends the high-speed rendering capabilities of 3D Gaussian Splatting (3DGS) to represent volumetric videos. However, the large number of Gaussians, substantial temporal redundancies, and…

Graphics · Computer Science 2026-01-14 Hyeongmin Lee , Kyungjune Baek

Constructing drivable and photorealistic 3D head avatars has become a central task in AR/XR, enabling immersive and expressive user experiences. With the emergence of high-fidelity and efficient representations such as 3D Gaussians, recent…

Graphics · Computer Science 2025-12-25 Jaeseong Lee , Junyeong Ahn , Taewoong Kang , Jaegul Choo

Creating high-quality 3D avatars using 3D Gaussian Splatting (3DGS) from a monocular video benefits virtual reality and telecommunication applications. However, existing automatic methods exhibit artifacts under novel poses due to limited…

Human-Computer Interaction · Computer Science 2024-12-23 Jotaro Sakamiya , I-Chao Shen , Jinsong Zhang , Mustafa Doga Dogan , Takeo Igarashi

We present LiftAvatar, a new paradigm that completes sparse monocular observations in kinematic space (e.g., facial expressions and head pose) and uses the completed signals to drive high-fidelity avatar animation. LiftAvatar is a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hualiang Wei , Shunran Jia , Jialun Liu , Wenhui Li

Recent advances in 3D Gaussian Splatting have allowed for real-time, high-fidelity novel view synthesis. Nonetheless, these models have significant storage requirements for large and medium-sized scenes, hindering their deployment over…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Diego Revilla , Pooja Suresh , Anand Bhojan , Ooi Wei Tsang

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

The field of novel-view synthesis has recently witnessed the emergence of 3D Gaussian Splatting, which represents scenes in a point-based manner and renders through rasterization. This methodology, in contrast to Radiance Fields that rely…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Fengyi Zhang , Yadan Luo , Tianjun Zhang , Lin Zhang , Zi Huang

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Bernhard Kerbl , Andréas Meuleman , Georgios Kopanas , Michael Wimmer , Alexandre Lanvin , George Drettakis

In this paper, we explore a reconstruction and reenactment separated framework for 3D Gaussians head, which requires only a single portrait image as input to generate controllable avatar. Specifically, we developed a large-scale one-shot…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Zhiling Ye , Cong Zhou , Xiubao Zhang , Haifeng Shen , Weihong Deng , Quan Lu

We propose a novel approach for reconstructing animatable 3D Gaussian avatars from monocular videos captured by commodity devices like smartphones. Photorealistic 3D head avatar reconstruction from such recordings is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jiapeng Tang , Davide Davoli , Tobias Kirschstein , Liam Schoneveld , Matthias Niessner

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin