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Sparse-view 3D Gaussian splatting seeks to render high-quality novel views of 3D scenes from a limited set of input images. While recent pose-free feed-forward methods leveraging pre-trained 3D priors have achieved impressive results, most…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Muyu Xu , Fangneng Zhan , Xiaoqin Zhang , Ling Shao , Shijian Lu

3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advantages, researchers have progressively extended 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Han Jiao , Jiakai Sun , Lei Zhao , Zhanjie Zhang , Wei Xing , Huaizhong Lin

Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Chao Wang , Krzysztof Wolski , Bernhard Kerbl , Ana Serrano , Mojtaba Bemana , Hans-Peter Seidel , Karol Myszkowski , Thomas Leimkühler

Generalized feed-forward Gaussian models have achieved significant progress in sparse-view 3D reconstruction by leveraging prior knowledge from large multi-view datasets. However, these models often struggle to represent high-frequency…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Seungtae Nam , Xiangyu Sun , Gyeongjin Kang , Younggeun Lee , Seungjun Oh , Eunbyung Park

We aim to address sparse-view reconstruction of a 3D scene by leveraging priors from large-scale vision models. While recent advancements such as 3D Gaussian Splatting (3DGS) have demonstrated remarkable successes in 3D reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Hanyang Yu , Xiaoxiao Long , Ping Tan

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu 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

Recently, Gaussian Splatting, a method that represents a 3D scene as a collection of Gaussian distributions, has gained significant attention in addressing the task of novel view synthesis. In this paper, we highlight a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Haoxuan Qu , Zhuoling Li , Hossein Rahmani , Yujun Cai , Jun Liu

Reconstructing objects from posed images is a crucial and complex task in computer graphics and computer vision. While NeRF-based neural reconstruction methods have exhibited impressive reconstruction ability, they tend to be…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Shuichang Lai , Letian Huang , Jie Guo , Kai Cheng , Bowen Pan , Xiaoxiao Long , Jiangjing Lyu , Chengfei Lv , Yanwen Guo

Although 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it still faces challenges such as aliasing, projection artifacts, and view inconsistencies, primarily due to the simplification of treating splats as 2D entities.…

Radiance field methods, such as Neural Radiance Field or 3D Gaussian Splatting, have emerged as seminal 3D representations for synthesizing realistic novel views. For practical applications, there is ongoing research on flexible scene…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Ji Hyun Seo , Byounhyun Yoo , Gerard Jounghyun Kim

3D Gaussian splatting has become a prominent technique for representing and rendering complex 3D scenes, due to its high fidelity and speed advantages. However, the growing demand for large-scale models calls for effective compression to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Boyuan Tian , Qizhe Gao , Siran Xianyu , Xiaotong Cui , Minjia Zhang

In this paper, we introduce a 3D Gaussian Splatting (3DGS)-based pipeline for stereo dataset generation, offering an efficient alternative to Neural Radiance Fields (NeRF)-based methods. To obtain useful geometry estimates, we explore…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Filip Slezak , Magnus K. Gjerde , Joakim B. Haurum , Ivan Nikolov , Morten S. Laursen , Thomas B. Moeslund

3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it suffers from a substantial memory footprint, particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Yangming Zhang , Jian Xu , Chaojian Li , Kunxiong Zhu , Wei Niu , Gagan Agrawal , Yang Katie Zhao , Jian Wang , Yingyan Celine Lin , Miao Yin

We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our framework, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Chongjie Ye , Yinyu Nie , Jiahao Chang , Yuantao Chen , Yihao Zhi , Xiaoguang Han

Recent advancements in radiance fields have opened new avenues for creating high-quality 3D assets and scenes. Style transfer can enhance these 3D assets with diverse artistic styles, transforming creative expression. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Sahil Jain , Avik Kuthiala , Prabhdeep Singh Sethi , Prakanshul Saxena

The recent introduction of 3D Gaussian Splatting (3DGS) has significantly advanced novel view synthesis. Several studies have further improved the rendering quality of 3DGS, yet they still exhibit noticeable visual discrepancies when…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Junseo Koo , Jinseo Jeong , Gunhee Kim