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Related papers: SRGS: Super-Resolution 3D Gaussian Splatting

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This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach for 3D reconstruction, providing explicit, point-based representations and enabling high-quality real time rendering. However, when trained with sparse input views,…

Image and Video Processing · Electrical Eng. & Systems 2026-02-09 Chaeyoung Jeong , Kwangsu Kim

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

We propose GRGS, a generalizable and relightable 3D Gaussian framework for high-fidelity human novel view synthesis under diverse lighting conditions. Unlike existing methods that rely on per-character optimization or ignore physical…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Yipengjing Sun , Shengping Zhang , Chenyang Wang , Shunyuan Zheng , Zonglin Li , Xiangyang Ji

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification where high-variance image regions are covered by a few large…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Jiahui Zhang , Fangneng Zhan , Muyu Xu , Shijian Lu , Eric Xing

Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance…

Graphics · Computer Science 2025-01-16 Meenakshi Krishnan , Liam Fowl , Ramani Duraiswami

3D Gaussian Splatting (3DGS) creates a radiance field consisting of 3D Gaussians to represent a scene. With sparse training views, 3DGS easily suffers from overfitting, negatively impacting rendering. This paper introduces a new…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jiawei Zhang , Jiahe Li , Xiaohan Yu , Lei Huang , Lin Gu , Jin Zheng , Xiao Bai

Recent advances in 3D Gaussian Splatting (3DGS) have enabled high-quality, real-time novel-view synthesis from multi-view images. However, most existing methods assume the object is captured in a single, static pose, resulting in incomplete…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Ting-Yu Yen , Yu-Sheng Chiu , Shih-Hsuan Hung , Peter Wonka , Hung-Kuo Chu

3D Gaussian Splatting (3DGS) has emerged as a preferred choice alongside Neural Radiance Fields (NeRF) in inverse rendering due to its superior rendering speed. Currently, the common approach in 3DGS is to utilize "single-view" mini-batch…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Minhyuk Choi , Injae Kim , Hyunwoo J. Kim

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Binbin Huang , Zehao Yu , Anpei Chen , Andreas Geiger , Shenghua Gao

3D Gaussian Splatting (3DGS) enables photorealistic rendering but suffers from artefacts due to sparse Structure-from-Motion (SfM) initialisation. To address this limitation, we propose GP-GS, a Gaussian Process (GP) based densification…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhihao Guo , Jingxuan Su , Chenghao Qian , Shenglin Wang , Jinlong Fan , Jing Zhang , Wei Zhou , Hadi Amirpour , Yunlong Zhao , Liangxiu Han , Peng Wang

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

Compared with previous 3D reconstruction methods like Nerf, recent Generalizable 3D Gaussian Splatting (G-3DGS) methods demonstrate impressive efficiency even in the sparse-view setting. However, the promising reconstruction performance of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Chuanrui Zhang , Yingshuang Zou , Zhuoling Li , Minmin Yi , Haoqian Wang

In this paper, we propose UniGS, a unified map representation and differentiable framework for high-fidelity multimodal 3D reconstruction based on 3D Gaussian Splatting. Our framework integrates a CUDA-accelerated rasterization pipeline…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yusen Xie , Zhenmin Huang , Jianhao Jiao , Dimitrios Kanoulas , Jun Ma

3D Gaussian Splatting (3DGS) is a new method for modeling and rendering 3D radiance fields that achieves much faster learning and rendering time compared to SOTA NeRF methods. However, it comes with a drawback in the much larger storage…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 KL Navaneet , Kossar Pourahmadi Meibodi , Soroush Abbasi Koohpayegani , Hamed Pirsiavash

Image-based 3D generation has vast applications in robotics and gaming, where high-quality, diverse outputs and consistent 3D representations are crucial. However, existing methods have limitations: 3D diffusion models are limited by…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Ye Tao , Jiawei Zhang , Yahao Shi , Dongqing Zou , Bin Zhou

Recently, 3D Gaussian Splatting (3DGS) provides a new framework for novel view synthesis, and has spiked a new wave of research in neural rendering and related applications. As 3DGS is becoming a foundational component of many models, any…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Jialin Zhu , Jiangbei Yue , Feixiang He , He Wang

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xiaoyang Lyu , Yang-Tian Sun , Yi-Hua Huang , Xiuzhe Wu , Ziyi Yang , Yilun Chen , Jiangmiao Pang , Xiaojuan Qi

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in 3D scene reconstruction. Beyond novel view synthesis, it shows great potential for multi-view surface reconstruction. Existing methods employ optimization-based…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Chensheng Dai , Shengjun Zhang , Min Chen , Yueqi Duan