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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

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

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an assumption that is often violated in real-world applications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhankuo Xu , Chaoran Feng , Yingtao Li , Jianbin Zhao , Jiashu Yang , Wangbo Yu , Li Yuan , Yonghong Tian

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

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

The recent surge in popularity of deep generative models for 3D objects has highlighted the need for more efficient training methods, particularly given the difficulties associated with training with conventional 3D representations, such as…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Adam Kania , Artur Kasymov , Jakub Kościukiewicz , Artur Górak , Marcin Mazur , Maciej Zięba , Przemysław Spurek

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

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

Neural Radiance Fields (NeRF) enable 3D scene reconstruction from 2D images and camera poses for Novel View Synthesis (NVS). Although NeRF can produce photorealistic results, it often suffers from overfitting to training views, leading to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Fusang Wang , Arnaud Louys , Nathan Piasco , Moussab Bennehar , Luis Roldão , Dzmitry Tsishkou

Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accurately in 3DGS remains challenging due to the discrete nature of Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Yi He , Tao Wang , Yi Jin , Congyan Lang , Yidong Li , Haibin Ling

We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering. Unlike recent rasterization based approach by 3D Gaussian Splatting (3DGS), our primitive based representation…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Alexander Mai , Peter Hedman , George Kopanas , Dor Verbin , David Futschik , Qiangeng Xu , Falko Kuester , Jonathan T. Barron , Yinda Zhang

We introduce GeMS, a framework for 3D Gaussian Splatting (3DGS) designed to handle severely motion-blurred images. State-of-the-art deblurring methods for extreme blur, such as ExBluRF, as well as Gaussian Splatting-based approaches like…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Gopi Raju Matta , Trisha Reddypalli , Vemunuri Divya Madhuri , Kaushik Mitra

Neural image representations have emerged as a promising approach for encoding and rendering visual data. Combined with learning-based workflows, they demonstrate impressive trade-offs between visual fidelity and memory footprint. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Yunxiang Zhang , Bingxuan Li , Alexandr Kuznetsov , Akshay Jindal , Stavros Diolatzis , Kenneth Chen , Anton Sochenov , Anton Kaplanyan , Qi Sun

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Miriam Jäger , Markus Hillemann , Boris Jutzi

While Gaussian Splatting (GS) demonstrates efficient and high-quality scene rendering and small area surface extraction ability, it falls short in handling large-scale aerial image surface extraction tasks. To overcome this, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Zhuoxiao Li , Shanliang Yao , Taoyu Wu , Yong Yue , Wufan Zhao , Rongjun Qin , Angel F. Garcia-Fernandez , Andrew Levers , Xiaohui Zhu

3D Gaussian Splatting has recently emerged as an efficient solution for high-quality and real-time novel view synthesis. However, its capability for accurate surface reconstruction remains underexplored. Due to the discrete and unstructured…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Qing Li , Huifang Feng , Xun Gong , Yu-Shen Liu

3D Gaussian Splatting (3DGS) has gained significant attention for their high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Sangyoun Lee

Novel View Synthesis (NVS) can reconstruct scenes from multi-view images and synthesize novel images from new viewpoints, which provides technical support for tasks such as target recognition and environmental perception. Aerial remote…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yiling Yao , Bing Zhang , Wenjuan Zhang , Lianru Gao , Dailiang Peng , Bocheng Li , Yaning Wang , Bowen Wang