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The 3D Gaussian splatting methods are getting popular. However, they work directly on the signal, leading to a dense representation of the signal. Even with some techniques such as pruning or distillation, the results are still dense. In…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yuanhao Gong

We propose a method to reconstruct dynamic fire in 3D from a limited set of camera views with a Gaussian-based spatiotemporal representation. Capturing and reconstructing fire and its dynamics is highly challenging due to its volatile…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jakob Nazarenus , Dominik Michels , Wojtek Palubicki , Simin Kou , Fang-Lue Zhang , Soren Pirk , Reinhard Koch

We proposed Precomputed RadianceTransfer of GaussianSplats (PRTGS), a real-time high-quality relighting method for Gaussian splats in low-frequency lighting environments that captures soft shadows and interreflections by precomputing 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Yijia Guo , Yuanxi Bai , Liwen Hu , Ziyi Guo , Mianzhi Liu , Yu Cai , Tiejun Huang , Lei Ma

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

Smoke in real-world scenes can severely degrade image quality and hamper visibility. Recent image restoration methods either rely on data-driven priors that are susceptible to hallucinations, or are limited to static low-density smoke. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Neham Jain , Andrew Jong , Sebastian Scherer , Ioannis Gkioulekas

Flame tomography is a compelling approach for extracting large amounts of data from experiments via 3-D thermochemical reconstruction. Recent efforts employing neural-network flame representations have suggested improved reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Nicolas Tricard , Zituo Chen , Sili Deng

In aerospace and energy engineering, accurate 3D combustion field temperature measurement is critical. The resolution of traditional methods based on algebraic iteration is limited by the initial voxel division. This study introduces a…

Image and Video Processing · Electrical Eng. & Systems 2024-05-13 Shenxiang Feng , Xiaojian Hao , Xiaodong Huang , Pan Pei , Tong Wei , Chenyang Xu

Particle-based representations of radiance fields such as 3D Gaussian Splatting have found great success for reconstructing and re-rendering of complex scenes. Most existing methods render particles via rasterization, projecting them to…

Decoupling lighting from geometry using unconstrained photo collections is notoriously challenging. Solving it would benefit many users as creating complex 3D assets takes days of manual labor. Many previous works have attempted to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Joanna Kaleta , Kacper Kania , Tomasz Trzcinski , Marek Kowalski

Gaussian Splatting has recently emerged as the go-to representation for reconstructing and rendering 3D scenes. The transition from 3D to 2D Gaussian primitives has further improved multi-view consistency and surface reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Sebastian Weiss , Derek Bradley

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 David Charatan , Sizhe Li , Andrea Tagliasacchi , Vincent Sitzmann

Rendering complex reflection of real-world scenes using 3D Gaussian splatting has been a quite promising solution for photorealistic novel view synthesis, but still faces bottlenecks especially in rendering speed and memory storage. This…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Chang Liu , Hongliang Yuan , Lianghao Zhang , Sichao Wang , Jianwei Guo , Shi-Sheng Huang

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

We present LiDAR-GS, a Gaussian Splatting (GS) method for real-time, high-fidelity re-simulation of LiDAR scans in public urban road scenes. Recent GS methods proposed for cameras have achieved significant advancements in real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qifeng Chen , Sheng Yang , Sicong Du , Tao Tang , Rengan Xie , Peng Chen , Yuchi Huo

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Saptarshi Neil Sinha , Holger Graf , Michael Weinmann

3D Gaussian Splatting (3DGS) has recently emerged as a powerful explicit representation enabling fast, high-fidelity rendering, making it a promising foundation for closed-loop simulators and perception models in autonomous driving.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Kota Shimomura , Hidehisa Arai , Tsubasa Takahashi , Takayoshi Yamashita , Hironobu Fujiyoshi

Efficient and robust 3D scene representation is crucial in autonomous driving, robotics, and related fields. While RGB images provide valuable content for 3D reconstruction, other modalities like thermal or depth can enable additional…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Manoj Biswanath , Chenxin Cai , Hannah Schieber , Daniel Roth , Benjamin Busam

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,…

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

We present Real-time Gaussian SLAM (RTG-SLAM), a real-time 3D reconstruction system with an RGBD camera for large-scale environments using Gaussian splatting. The system features a compact Gaussian representation and a highly efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Zhexi Peng , Tianjia Shao , Yong Liu , Jingke Zhou , Yin Yang , Jingdong Wang , Kun Zhou
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