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Related papers: SmokeGS-R: Physics-Guided Pseudo-Clean 3DGS for Re…

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This paper describes our method for Track 2 of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge on smoke-degraded images. In this task, smoke reduces image visibility and weakens the cross-view consistency required by scene…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Qida Cao , Xinyuan Hu , Changyue Shi , Jiajun Ding , Zhou Yu , Jun Yu

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

Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-dependent appearance changes, and severe degradation of cross-view consistency. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Xinye Zheng , Fei Wang , Yiqi Nie , Kun Li , Junjie Chen , Jiaqi Zhao , Yanyan Wei , Zhiliang Wu

Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3D-GS). Despite recent progress, these tasks are often addressed independently, with GS-based rendering methods struggling under…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Qingyuan Zhou , Yuehu Gong , Weidong Yang , Jiaze Li , Yeqi Luo , Baixin Xu , Shuhao Li , Ben Fei , Ying He

This paper presents our approach to the NTIRE 2026 3D Restoration and Reconstruction Challenge (Track 1), which focuses on reconstructing high-quality 3D representations from degraded multi-view inputs. The challenge involves recovering…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yuhao Liu , Dingju Wang , Ziyang Zheng

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

Reconstructing dynamic fluids from sparse views is a long-standing and challenging problem, due to the severe lack of 3D information from insufficient view coverage. While several pioneering approaches have attempted to address this issue…

Graphics · Computer Science 2026-04-14 Chen Li , Shanshan Dong , Sheng Qiu , Jianmin Han , Yibo Zhao , Zan Gao , Taku Komura , Kemeng Huang

We propose a pipeline to extract and reconstruct dynamic 3D smoke assets from a single in-the-wild video, and further integrate interactive simulation for smoke design and editing. Recent developments in 3D vision have significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Yuqiu Liu , Jialin Song , Manolis Savva , Wuyang Chen

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

Recently, 3D Gaussian Splatting (3DGS) has reshaped the field of photorealistic 3D reconstruction, achieving impressive rendering quality and speed. However, when applied to large-scale street scenes, existing methods suffer from rapidly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Guangting Zheng , Jiajun Deng , Xiaomeng Chu , Yu Yuan , Houqiang Li , Yanyong Zhang

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,…

Recent 3D Gaussian Splatting (3DGS) methods have demonstrated the feasibility of self-driving scene reconstruction and novel view synthesis. However, most existing methods either rely solely on cameras or use LiDAR only for Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 ZY Chen , F Zhu , H Zhu , DY Kong , XK Kuang , YJ Zhang , CM Jiang

3D Gaussian Splatting (3DGS) creates a radiance field consisting of 3D Gaussians to represent a scene. With sparse training views, 3DGS easily suffers from overfitting, negatively impacting rendering. This paper introduces a new…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jiawei Zhang , Jiahe Li , Xiaohan Yu , Lei Huang , Lin Gu , Jin Zheng , Xiao Bai

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

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

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to identify robust reconstruction pipelines that are robust…

3D Gaussian Splatting (3DGS) has shown a powerful capability for novel view synthesis due to its detailed expressive ability and highly efficient rendering speed. Unfortunately, creating relightable 3D assets and reconstructing faithful…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Zuo-Liang Zhu , Beibei Wang , Jian Yang

In recent years, 3D Gaussian splatting (3DGS) has achieved remarkable progress in novel view synthesis. However, accurately reconstructing glossy surfaces under complex illumination remains challenging, particularly in scenes with strong…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Ningjing Fan , Yiqun Wang

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
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