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Reconstructing 3D scenes and synthesizing novel views has seen rapid progress in recent years. Neural Radiance Fields demonstrated that continuous volumetric radiance fields can achieve high-quality image synthesis, but their long training…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Jan Held , Renaud Vandeghen , Sanghyun Son , Daniel Rebain , Matheus Gadelha , Yi Zhou , Ming C. Lin , Marc Van Droogenbroeck , Andrea Tagliasacchi

The field of computer graphics was revolutionized by models such as Neural Radiance Fields and 3D Gaussian Splatting, displacing triangles as the dominant representation for photogrammetry. In this paper, we argue for a triangle comeback.…

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

Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicated geometry and topology, and generating novel views of a…

Graphics · Computer Science 2024-02-08 Lin Gao , Jie Yang , Bo-Tao Zhang , Jia-Mu Sun , Yu-Jie Yuan , Hongbo Fu , Yu-Kun Lai

3D Gaussian Splatting (3DGS) has enabled high-fidelity virtualization with fast rendering and optimization for novel view synthesis. On the other hand, triangle mesh models still remain a popular choice for surface reconstruction but suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Xinpeng Liu , Fumio Okura

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

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain incompatible with mesh-based pipelines that power AR/VR and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jan Held , Sanghyun Son , Renaud Vandeghen , Daniel Rebain , Matheus Gadelha , Yi Zhou , Anthony Cioppa , Ming C. Lin , Marc Van Droogenbroeck , Andrea Tagliasacchi

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

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

Neural 3D representations such as Neural Radiance Fields (NeRF), excel at producing photo-realistic rendering results but lack the flexibility for manipulation and editing which is crucial for content creation. Previous works have attempted…

Graphics · Computer Science 2025-03-25 Xiangjun Gao , Xiaoyu Li , Yiyu Zhuang , Qi Zhang , Wenbo Hu , Chaopeng Zhang , Yao Yao , Ying Shan , Long Quan

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

Gaussian Splatting (GS) is a recent and pivotal technique in 3D computer graphics. GS-based algorithms almost always bypass classical methods such as ray tracing, which offer numerous inherent advantages for rendering. For example, ray…

3D Gaussian Splatting (3DGS) has emerged as a leading approach for high-quality novel view synthesis, with numerous variants extending its applicability to a broad spectrum of 3D and 4D scene reconstruction tasks. Despite its success, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiming Wang , Shaofei Wang , Marko Mihajlovic , Siyu Tang

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

Since its introduction, 3D Gaussian Splatting (3DGS) has become an important reference method for learning 3D representations of a captured scene, allowing real-time novel-view synthesis with high visual quality and fast training times.…

Graphics · Computer Science 2025-02-27 Adam Celarek , George Kopanas , George Drettakis , Michael Wimmer , Bernhard Kerbl

2D Gaussian Splatting (2DGS) has recently emerged as a promising method for novel view synthesis and surface reconstruction, offering better view-consistency and geometric accuracy than volumetric 3DGS. However, 2DGS suffers from severe…

Graphics · Computer Science 2025-11-04 Mae Younes , Adnane Boukhayma

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

Recent advancements in neural rendering techniques have significantly enhanced the fidelity of 3D reconstruction. Notably, the emergence of 3D Gaussian Splatting (3DGS) has marked a significant milestone by adopting a discrete scene…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Licheng Shen , Ho Ngai Chow , Lingyun Wang , Tong Zhang , Mengqiu Wang , Yuxing Han

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

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
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