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Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

We present LiDAR-GS, a Gaussian Splatting (GS) method for real-time, high-fidelity re-simulation of LiDAR scans in public urban road scenes. Recent GS methods proposed for cameras have achieved significant advancements in real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qifeng Chen , Sheng Yang , Sicong Du , Tao Tang , Rengan Xie , Peng Chen , Yuchi Huo

Vast and high-quality data are essential for end-to-end autonomous driving systems. However, current driving data is mainly collected by vehicles, which is expensive and inefficient. A potential solution lies in synthesizing data from…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Jialei Chen , Wuhao Xu , Sipeng He , Baoru Huang , Dongchun Ren

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

3D Gaussian Splatting (3DGS) has recently emerged as an innovative and efficient 3D representation technique. While its potential for extended reality (XR) applications is frequently highlighted, its practical effectiveness remains…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Shi Qiu , Binzhu Xie , Qixuan Liu , Pheng-Ann Heng

Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Jingqian Wu , Shuo Zhu , Chutian Wang , Boxin Shi , Edmund Y. Lam

3D Gaussian splatting (3D-GS) is a new rendering approach that outperforms the neural radiance field (NeRF) in terms of both speed and image quality. 3D-GS represents 3D scenes by utilizing millions of 3D Gaussians and projects these…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Joongho Jo , Hyeongwon Kim , Jongsun Park

We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneous spatial and spectral renderings by encoding material…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Christopher Thirgood , Oscar Mendez , Erin Chao Ling , Jon Storey , Simon Hadfield

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

Radiance field-based rendering methods have attracted significant interest from the computer vision and computer graphics communities. They enable high-fidelity rendering with complex real-world lighting effects, but at the cost of high…

Graphics · Computer Science 2026-01-23 Yinghan Xu , Théo Morales , John Dingliana

Free-viewpoint video (FVV) enables immersive viewing experiences by allowing users to view scenes from arbitrary perspectives. As a prominent reconstruction technique for FVV generation, 4D Gaussian Splatting (4DGS) models dynamic scenes…

Graphics · Computer Science 2025-12-25 Zhe Wang , Jinghang Li , Yifei Zhu

3D Gaussian Splatting (3DGS) has emerged as a powerful and efficient 3D representation for novel view synthesis. This paper extends 3DGS capabilities to inpainting, where masked objects in a scene are replaced with new contents that blend…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Mingxuan Cui , Qing Guo , Yuyi Wang , Hongkai Yu , Di Lin , Qin Zou , Ming-Ming Cheng , Xi Li

High dynamic range novel view synthesis (HDR-NVS) reconstructs scenes with dynamic details by fusing multi-exposure low dynamic range (LDR) views, yet it struggles to capture ambient illumination-dependent appearance. Implicitly supervising…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Huimin Zeng , Yue Bai , Hailing Wang , Yun Fu

Sparse-view scene reconstruction often faces significant challenges due to the constraints imposed by limited observational data. These limitations result in incomplete information, leading to suboptimal reconstructions using existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xiangyu Sun , Runnan Chen , Mingming Gong , Dong Xu , Tongliang Liu

Real-time visualization of large-scale volumetric data remains challenging, as direct volume rendering and voxel-based methods suffer from prohibitively high computational cost. We propose Variable Basis Mapping (VBM), a framework that…

Graphics · Computer Science 2026-01-15 Qibiao Li , Yuxuan Wang , Youcheng Cai , Huangsheng Du , Ligang Liu

Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following the pioneering work of 3D-GS, several methods have attempted…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Evangelos Ververas , Rolandos Alexandros Potamias , Jifei Song , Jiankang Deng , Stefanos Zafeiriou

Sensor simulation is pivotal for scalable validation of autonomous driving systems, yet existing Neural Radiance Fields (NeRF) based methods face applicability and efficiency challenges in industrial workflows. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Xianming Zeng , Sicong Du , Qifeng Chen , Lizhe Liu , Haoyu Shu , Jiaxuan Gao , Jiarun Liu , Jiulong Xu , Jianyun Xu , Mingxia Chen , Yiru Zhao , Peng Chen , Yapeng Xue , Chunming Zhao , Sheng Yang , Qiang Li

In this paper, we introduce Textured-GS, an innovative method for rendering Gaussian splatting that incorporates spatially defined color and opacity variations using Spherical Harmonics (SH). This approach enables each Gaussian to exhibit a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Zhentao Huang , Minglun Gong

Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3D-GS). Despite recent progress, these tasks are often addressed independently, with GS-based rendering methods struggling under…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Qingyuan Zhou , Yuehu Gong , Weidong Yang , Jiaze Li , Yeqi Luo , Baixin Xu , Shuhao Li , Ben Fei , Ying He

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel
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