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Reconstructing dynamic 3D scenes with photorealistic detail and strong temporal coherence remains a significant challenge. Existing Gaussian splatting approaches for dynamic scene modeling often rely on per-frame optimization, which can…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Tingxuan Huang , Haowei Zhu , Jun-hai Yong , Hao Pan , Bin Wang

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D geometry or mediocre rendering quality due to improper…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yuxuan Mu , Xinxin Zuo , Chuan Guo , Yilin Wang , Juwei Lu , Xiaofeng Wu , Songcen Xu , Peng Dai , Youliang Yan , Li Cheng

Sparse-view 3D reconstruction is a major challenge in computer vision, aiming to create complete three-dimensional models from limited viewing angles. Key obstacles include: 1) a small number of input images with inconsistent information;…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Bi'an Du , Lingbei Meng , Wei Hu

Recent years have witnessed substantial advancements in the field of 3D reconstruction from 2D images, particularly following the introduction of the neural radiance field (NeRF) technique. However, reconstructing a 3D high dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jiahao Wu , Lu Xiao , Rui Peng , Kaiqiang Xiong , Ronggang Wang

Low-light 3D reconstruction from sparse views remains challenging due to exposure imbalance and degraded color fidelity. While existing methods struggle with view inconsistency and require per-scene training, we propose SplatBright, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yue Wen , Liang Song , Hesheng Wang

3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precisely known camera poses, which are rarely available in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zongqi He , Hanmin Li , Kin-Chung Chan , Yushen Zuo , Hao Xie , Zhe Xiao , Jun Xiao , Kin-Man Lam

Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). Such solutions use GS to represent the scene's structure and the neural network to model dynamics. Such…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Joanna Kaleta , Sławomir Tadeja , Przemysław Spurek

Rendering dynamic scenes from monocular videos is a crucial yet challenging task. The recent deformable Gaussian Splatting has emerged as a robust solution to represent real-world dynamic scenes. However, it often leads to heavily redundant…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Hanyang Kong , Xingyi Yang , Xinchao Wang

Generalizable Gaussian Splatting aims to synthesize novel views for unseen scenes without per-scene optimization. In particular, recent advancements utilize feed-forward networks to predict per-pixel Gaussian parameters, enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Yuxi Hu , Jun Zhang , Kuangyi Chen , Zhe Zhang , Friedrich Fraundorfer

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

Professional color editing requires precise control over both color (hue and saturation) and lightness, ideally through separate, independent controls. We present a real-time interactive color editing framework for 3D Gaussian Splatting…

Graphics · Computer Science 2026-04-03 Cheng-Kang Ted Chao , Yotam Gingold

This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such as requiring precise camera poses for input and dense…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Chong Cheng , Gaochao Song , Yiyang Yao , Qinzheng Zhou , Gangjian Zhang , Hao Wang

Recent advancements in 3D reconstruction from single images have been driven by the evolution of generative models. Prominent among these are methods based on Score Distillation Sampling (SDS) and the adaptation of diffusion models in the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Zi-Xin Zou , Zhipeng Yu , Yuan-Chen Guo , Yangguang Li , Ding Liang , Yan-Pei Cao , Song-Hai Zhang

Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiaqi Lin , Zhihao Li , Xiao Tang , Jianzhuang Liu , Shiyong Liu , Jiayue Liu , Yangdi Lu , Xiaofei Wu , Songcen Xu , Youliang Yan , Wenming Yang

In this paper, we address common error sources for 3D Gaussian Splatting (3DGS) including blur, imperfect camera poses, and color inconsistencies, with the goal of improving its robustness for practical applications like reconstructions…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 François Darmon , Lorenzo Porzi , Samuel Rota-Bulò , Peter Kontschieder

Recent advancements in 3D Gaussian Splatting (3D-GS) have established new benchmarks for rendering quality and efficiency in 3D reconstruction. However, 3D-GS faces critical limitations when generating novel views that significantly deviate…

Graphics · Computer Science 2025-03-05 Yifei Gao , Kerui Ren , Jie Ou , Lei Wang , Jiaji Wu , Jun Cheng

Gaussian Splatting (GS) has proven to be highly effective in novel view synthesis, achieving high-quality and real-time rendering. However, its potential for reconstructing detailed 3D shapes has not been fully explored. Existing methods…

Graphics · Computer Science 2024-06-25 Baowen Zhang , Chuan Fang , Rakesh Shrestha , Yixun Liang , Xiaoxiao Long , Ping Tan

Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Chao Wang , Krzysztof Wolski , Bernhard Kerbl , Ana Serrano , Mojtaba Bemana , Hans-Peter Seidel , Karol Myszkowski , Thomas Leimkühler

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality, sharp images and accurate camera poses. Fulfilling these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Wangbo Yu , Chaoran Feng , Jiye Tang , Jiashu Yang , Zhenyu Tang , Xu Jia , Yuchao Yang , Li Yuan , Yonghong Tian