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Related papers: RainyGS: Efficient Rain Synthesis with Physically-…

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We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics pipelines can produce realistic fire effects but rely on handcrafted geometry,…

Reconstruction under adverse rainy conditions poses significant challenges due to reduced visibility and the distortion of visual perception. These conditions can severely impair the quality of geometric maps, which is essential for…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Shuhong Liu , Xiang Chen , Hongming Chen , Quanfeng Xu , Mingrui Li

For tasks such as urban digital twins, VR/AR/game scene design, or creating synthetic films, the traditional industrial approach often involves manually modeling scenes and using various rendering engines to complete the rendering process.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Chen Sang , Yeqiang Qian , Jiale Zhang , Chunxiang Wang , Ming Yang

Adverse climate conditions pose significant challenges for autonomous systems, demanding reliable perception and decision-making across diverse environments. To better simulate these conditions, physically-based NeRF rendering methods have…

Graphics · Computer Science 2025-03-20 Yuezhen Xie , Meiying Zhang , Qi Hao

3D Gaussian Splatting (3DGS) under raindrop conditions suffers from severe occlusions and optical distortions caused by raindrop contamination on the camera lens, substantially degrading reconstruction quality. Existing benchmarks typically…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhiqiang Teng , Tingting Chen , Beibei Lin , Zifeng Yuan , Xuanyi Li , Xuanyu Zhang , Shunli Zhang

3D Gaussian Splatting (3DGS) has gained significant attention for 3D scene reconstruction, but still suffers from complex outdoor environments, especially under adverse weather. This is because 3DGS treats the artifacts caused by adverse…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Chenghao Qian , Yuhu Guo , Wenjing Li , Gustav Markkula

3D Gaussian Splatting (3DGS) has established itself as a leading technique for 3D reconstruction and novel view synthesis of static scenes, achieving outstanding rendering quality and fast training. However, the method does not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Margherita Lea Corona , Wieland Morgenstern , Peter Eisert , Anna Hilsmann

Reconstructing dynamic scenes with large-scale and complex motions remains a significant challenge. Recent techniques like Neural Radiance Fields and 3D Gaussian Splatting (3DGS) have shown promise but still struggle with scenes involving…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Qiankun Gao , Yanmin Wu , Chengxiang Wen , Jiarui Meng , Luyang Tang , Jie Chen , Ronggang Wang , Jian Zhang

Scene view synthesis, which generates novel views from limited perspectives, is increasingly vital for applications like virtual reality, augmented reality, and robotics. Unlike object-based tasks, such as generating 360{\deg} views of a…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Xiaofeng Jin , Yan Fang , Matteo Frosi , Jianfei Ge , Jiangjian Xiao , Matteo Matteucci

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

Rain fills the atmosphere with water particles, which breaks the common assumption that light travels unaltered from the scene to the camera. While it is well-known that rain affects computer vision algorithms, quantifying its impact is…

Computer Vision and Pattern Recognition · Computer Science 2020-09-09 Maxime Tremblay , Shirsendu Sukanta Halder , Raoul de Charette , Jean-François Lalonde

Image data captured outdoors often exhibit unbounded scenes and unconstrained, varying lighting conditions, making it challenging to decompose them into geometry, reflectance, and illumination. Recent works have focused on achieving this…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Lianjun Liao , Chunhui Zhang , Tong Wu , Henglei Lv , Bailin Deng , Lin Gao

Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Jingqian Wu , Shuo Zhu , Chutian Wang , Boxin Shi , Edmund Y. Lam

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

Novel view synthesis of urban scenes is essential for autonomous driving-related applications.Existing NeRF and 3DGS-based methods show promising results in achieving photorealistic renderings but require slow, per-scene optimization. We…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Sheng Miao , Jiaxin Huang , Dongfeng Bai , Xu Yan , Hongyu Zhou , Yue Wang , Bingbing Liu , Andreas Geiger , Yiyi Liao

To improve the robustness to rain, we present a physically-based rain rendering pipeline for realistically inserting rain into clear weather images. Our rendering relies on a physical particle simulator, an estimation of the scene lighting…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Shirsendu Sukanta Halder , Jean-François Lalonde , Raoul de Charette

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

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