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Recent studies have combined 3D Gaussian and 3D Morphable Models (3DMM) to construct high-quality 3D head avatars. In this line of research, existing methods either fail to capture the dynamic textures or incur significant overhead in terms…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Yating Wang , Xuan Wang , Ran Yi , Yanbo Fan , Jichen Hu , Jingcheng Zhu , Lizhuang Ma

Video representation is a long-standing problem that is crucial for various down-stream tasks, such as tracking,depth prediction,segmentation,view synthesis,and editing. However, current methods either struggle to model complex motions due…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Yang-Tian Sun , Yi-Hua Huang , Lin Ma , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

Recovering the intrinsic physical attributes of a scene from images, generally termed as the inverse rendering problem, has been a central and challenging task in computer vision and computer graphics. In this paper, we present GUS-IR, a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhihao Liang , Hongdong Li , Kui Jia , Kailing Guo , Qi Zhang

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Haoxuan Qu , Yujun Cai , Hossein Rahmani , Ajay Kumar , Junsong Yuan , Jun Liu

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek to leverage Gaussian splatting to generate realistic…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Ye Yuan , Xueting Li , Yangyi Huang , Shalini De Mello , Koki Nagano , Jan Kautz , Umar Iqbal

3D Gaussian Splatting (3DGS) has made significant strides in novel view synthesis but is limited by the substantial number of Gaussian primitives required, posing challenges for deployment on lightweight devices. Recent methods address this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Zhengqing Gao , Dongting Hu , Jia-Wang Bian , Huan Fu , Yan Li , Tongliang Liu , Mingming Gong , Kun Zhang

Transmissive scenes are ubiquitous in daily life, yet reconstructing and rendering them remains highly challenging due to the inherent entanglement between near-field reflections from the surrounding environment on the transmissive surface,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhenyu Liang , Xiao Zhang , Tianchao Li , Jack C. P. Cheng , Chi-Keung Tang

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

The scale diversity of point cloud data presents significant challenges in developing unified representation learning techniques for 3D vision. Currently, there are few unified 3D models, and no existing pre-training method is equally…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Ziyi Wang , Yanran Zhang , Jie Zhou , Jiwen Lu

Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene using an RGB-D camera on a mobile platform. We propose a…

Robotics · Computer Science 2025-04-09 Liren Jin , Xingguang Zhong , Yue Pan , Jens Behley , Cyrill Stachniss , Marija Popović

3D Gaussian Splatting has gained widespread adoption across diverse applications due to its exceptional rendering performance and visual quality. While most existing methods rely on rasterization to render Gaussians, recent research has…

Graphics · Computer Science 2026-01-29 Junseo Lee , Sangyun Jeon , Jungi Lee , Junyong Park , Jaewoong Sim

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

In production rendering systems, caustics are typically rendered via photon mapping and gathering, a process often hindered by insufficient photon density. In this paper, we propose a novel photon guiding method to improve the photon…

Graphics · Computer Science 2024-08-07 Jiawei Huang , Hajime Tanaka , Taku Komura , Yoshifumi Kitamura

Typical inverse rendering methods focus on learning implicit neural scene representations by modeling the geometry, materials and illumination separately, which entails significant computations for optimization. In this work we design a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Shuang Wu , Songlin Tang , Guangming Lu , Jianzhuang Liu , Wenjie Pei

We propose two novel ideas (adoption of deferred rendering and mesh-based representation) to improve the quality of 3D Gaussian splatting (3DGS) based inverse rendering. We first report a problem incurred by hidden Gaussians, where…

Graphics · Computer Science 2024-09-17 Euntae Choi , Sungjoo Yoo

3D Gaussian Splatting (3DGS) is a recent approach for scene rendering. Although primarily designed for view synthesis, its potential for scene understanding tasks remains underexplored. In this work, we conduct a comparative evaluation of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Julia Farganus , Krzysztof Żurawicki , Arkadiusz Gaweł , Weronika Jakubowska , Halina Kwaśnicka

Recent approaches representing 3D objects and scenes using Gaussian splats show increased rendering speed across a variety of platforms and devices. While rendering such representations is indeed extremely efficient, storing and…

Graphics · Computer Science 2024-07-01 Junli Cao , Vidit Goel , Chaoyang Wang , Anil Kag , Ju Hu , Sergei Korolev , Chenfanfu Jiang , Sergey Tulyakov , Jian Ren

Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiaqi Lin , Zhihao Li , Xiao Tang , Jianzhuang Liu , Shiyong Liu , Jiayue Liu , Yangdi Lu , Xiaofei Wu , Songcen Xu , Youliang Yan , Wenming Yang
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