English
Related papers

Related papers: 3D Gaussian as a New Era: A Survey

200 papers

The 3D Gaussian Splatting (3D-GS) is a novel method for scene representation and view synthesis. Although Scaffold-GS achieves higher quality real-time rendering compared to the original 3D-GS, its fine-grained rendering of the scene is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Chenyang Xu , XingGuo Deng , Rui Zhong

Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have advanced 3D reconstruction and novel view synthesis, but remain heavily dependent on accurate camera poses and dense viewpoint coverage. These requirements limit their…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiahui Lu , Haihong Xiao , Xueyan Zhao , Wenxiong Kang

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Florian Hahlbohm , Linus Franke , Martin Eisemann , Marcus Magnor

We leverage repetitive elements in 3D scenes to improve novel view synthesis. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have greatly improved novel view synthesis but renderings of unseen and occluded parts remain…

We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that primarily perform novel-view synthesis from a sparse set of constrained images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Wongi Park , Jordan A. James , Myeongseok Nam , Minjae Lee , Soomok Lee , Sang-Hyun Lee , William J. Beksi

Differentiable 3D-Gaussian splatting (GS) is emerging as a prominent technique in computer vision and graphics for reconstructing 3D scenes. GS represents a scene as a set of 3D Gaussians with varying opacities and employs a computationally…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Ziyuan Qu , Omkar Vengurlekar , Mohamad Qadri , Kevin Zhang , Michael Kaess , Christopher Metzler , Suren Jayasuriya , Adithya Pediredla

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jan Held , Renaud Vandeghen , Abdullah Hamdi , Adrien Deliege , Anthony Cioppa , Silvio Giancola , Andrea Vedaldi , Bernard Ghanem , Marc Van Droogenbroeck

3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However, current methods require highly controlled environments (no…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Sara Sabour , Lily Goli , George Kopanas , Mark Matthews , Dmitry Lagun , Leonidas Guibas , Alec Jacobson , David J. Fleet , Andrea Tagliasacchi

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

In this study, we present an end-to-end pipeline capable of converting drone-captured video streams into high-fidelity 3D reconstructions with minimal latency. Unmanned aerial vehicles (UAVs) are extensively used in aerial real-time…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Christos Maikos , Georgios Angelidis , Georgios Th. Papadopoulos

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

The photorealistic reconstruction and rendering of architectural scenes have extensive applications in industries such as film, games, and transportation. It also plays an important role in urban planning, architectural design, and the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Ruizhe Wang , Chunliang Hua , Tomakayev Shingys , Mengyuan Niu , Qingxin Yang , Lizhong Gao , Yi Zheng , Junyan Yang , Qiao Wang

Latent scene representation plays a significant role in training reinforcement learning (RL) agents. To obtain good latent vectors describing the scenes, recent works incorporate the 3D-aware latent-conditioned NeRF pipeline into scene…

Robotics · Computer Science 2024-09-30 Jiaxu Wang , Ziyi Zhang , Qiang Zhang , Jia Li , Jingkai Sun , Mingyuan Sun , Junhao He , Renjing Xu

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

While neural rendering has demonstrated impressive capabilities in 3D scene reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and accurate camera poses. Numerous approaches have been proposed to train…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Lingzhe Zhao , Peng Wang , Peidong Liu

Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However, it may require a large number of Gaussians, which creates a substantial memory footprint. This paper introduces GES (Generalized…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Abdullah Hamdi , Luke Melas-Kyriazi , Jinjie Mai , Guocheng Qian , Ruoshi Liu , Carl Vondrick , Bernard Ghanem , Andrea Vedaldi

Referenced-based scene stylization that edits the appearance based on a content-aligned reference image is an emerging research area. Starting with a pretrained neural radiance field (NeRF), existing methods typically learn a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yiqun Mei , Jiacong Xu , Vishal M. Patel

Recently, 3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results, while allowing the rendering of high-resolution images in real-time. However, leveraging 3D Gaussians for surface reconstruction poses…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Zehao Yu , Torsten Sattler , Andreas Geiger

The recent Gaussian Splatting achieves high-quality and real-time novel-view synthesis of the 3D scenes. However, it is solely concentrated on the appearance and geometry modeling, while lacking in fine-grained object-level scene…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Mingqiao Ye , Martin Danelljan , Fisher Yu , Lei Ke

3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang