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Novel view synthesis has been greatly enhanced by the development of radiance field methods. The introduction of 3D Gaussian Splatting (3DGS) has effectively addressed key challenges, such as long training times and slow rendering speeds,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Gopi Raju Matta , Reddypalli Trisha , Kaushik Mitra

3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. In recent times, some work has emerged that aims to extend…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Shijie Zhou , Haoran Chang , Sicheng Jiang , Zhiwen Fan , Zehao Zhu , Dejia Xu , Pradyumna Chari , Suya You , Zhangyang Wang , Achuta Kadambi

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

Recent advances in novel view synthesis have demonstrated impressive results in fast photorealistic scene rendering through differentiable point rendering, either via Gaussian Splatting (3DGS) [Kerbl and Kopanas et al. 2023] or neural point…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Linus Franke , Laura Fink , Marc Stamminger

An excellent representation is crucial for reinforcement learning (RL) performance, especially in vision-based reinforcement learning tasks. The quality of the environment representation directly influences the achievement of the learning…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Jiaxu Wang , Qiang Zhang , Jingkai Sun , Jiahang Cao , Gang Han , Wen Zhao , Weining Zhang , Yecheng Shao , Yijie Guo , Renjing Xu

Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D representations with semantic information for downstream…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Mihnea-Bogdan Jurca , Remco Royen , Ion Giosan , Adrian Munteanu

Surgical reconstruction of dynamic tissues from endoscopic videos is a crucial technology in robot-assisted surgery. The development of Neural Radiance Fields (NeRFs) has greatly advanced deformable tissue reconstruction, achieving…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Wenfeng Huang , Xiangyun Liao , Yinling Qian , Hao Liu , Yongming Yang , Wenjing Jia , Qiong Wang

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

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

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

Photo-realistic image rendering from 3D scene reconstruction has advanced significantly with neural rendering techniques. Among these, 3D Gaussian Splatting (3D-GS) outperforms Neural Radiance Fields (NeRFs) in quality and speed but…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Haolin Li , Jinyang Liu , Mario Sznaier , Octavia Camps

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from underfitting with blurred renderings on large-scale scenes due to limited model capacity. Recent approaches propose to geographically divide the scene and adopt…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Linning Xu , Yuanbo Xiangli , Sida Peng , Xingang Pan , Nanxuan Zhao , Christian Theobalt , Bo Dai , Dahua Lin

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

Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yunzhou Song , Heguang Lin , Jiahui Lei , Lingjie Liu , Kostas Daniilidis

NeRF-based 3D-aware Generative Adversarial Networks (GANs) like EG3D or GIRAFFE have shown very high rendering quality under large representational variety. However, rendering with Neural Radiance Fields poses challenges for 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Florian Barthel , Arian Beckmann , Wieland Morgenstern , Anna Hilsmann , Peter Eisert

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

3D Gaussian Splatting has gained widespread adoption across diverse applications due to its exceptional rendering performance and visual quality. While most existing methods rely on rasterization to render Gaussians, recent research has…

Graphics · Computer Science 2026-01-29 Junseo Lee , Sangyun Jeon , Jungi Lee , Junyong Park , Jaewoong Sim

Novel view synthesis has advanced significantly with the development of neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS). However, achieving high quality without compromising real-time rendering remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

3D Gaussian Splatting (3DGS) has become the de facto method of 3D representation in many vision tasks. This calls for the 3D understanding directly in this representation space. To facilitate the research in this direction, we first build…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Qi Ma , Yue Li , Bin Ren , Nicu Sebe , Ender Konukoglu , Theo Gevers , Luc Van Gool , Danda Pani Paudel