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This work focuses on modeling dynamic urban environments for autonomous driving simulation. Contemporary data-driven methods using neural radiance fields have achieved photorealistic driving scene modeling, but they suffer from low…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Guile Wu , Dongfeng Bai , Bingbing Liu

In this paper, we explore the existing challenges in 3D artistic scene generation by introducing ART3D, a novel framework that combines diffusion models and 3D Gaussian splatting techniques. Our method effectively bridges the gap between…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Pengzhi Li , Chengshuai Tang , Qinxuan Huang , Zhiheng Li

3D Gaussian Splatting has emerged as a powerful 3D scene representation technique, capturing fine details with high efficiency. In this paper, we introduce a novel voting-based method that extends 2D segmentation models to 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Joji Joseph , Bharadwaj Amrutur , Shalabh Bhatnagar

Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D representations with semantic information for downstream…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Mihnea-Bogdan Jurca , Remco Royen , Ion Giosan , Adrian Munteanu

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

High-quality novel view synthesis for large-scale scenes presents a challenging dilemma in 3D computer vision. Existing methods typically partition large scenes into multiple regions, reconstruct a 3D representation using Gaussian splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Xiaohan Zhang , Sitong Wang , Yushen Yan , Yi Yang , Mingda Xu , Qi Liu

With the emergence of Gaussian Splats, recent efforts have focused on large-scale scene geometric reconstruction. However, most of these efforts either concentrate on memory reduction or spatial space division, neglecting information in the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Butian Xiong , Xiaoyu Ye , Tze Ho Elden Tse , Kai Han , Shuguang Cui , Zhen Li

While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifacts that hinder accurate spatial data exploration.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Beizhen Zhao , Yifan Zhou , Gaochao Song , Ziran Yin , Hao Wang

Despite the substantial progress of novel view synthesis, existing methods, either based on the Neural Radiance Fields (NeRF) or more recently 3D Gaussian Splatting (3DGS), suffer significant degradation when the input becomes sparse.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Rui Peng , Wangze Xu , Luyang Tang , Liwei Liao , Jianbo Jiao , Ronggang Wang

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

3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D representation, bridging the gap between point clouds and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Wenyuan Zhang , Yu-Shen Liu

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

3D Gaussian Splatting (3DGS) has become horsepower in high-quality, real-time rendering for novel view synthesis of 3D scenes. However, existing methods focus primarily on geometric and appearance modeling, lacking deeper scene…

Graphics · Computer Science 2025-07-01 Minchao Jiang , Shunyu Jia , Jiaming Gu , Xiaoyuan Lu , Guangming Zhu , Anqi Dong , Liang Zhang

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

Given the growing need for automatic 3D content creation pipelines, various 3D representations have been studied to generate 3D objects from a single image. Due to its superior rendering efficiency, 3D Gaussian splatting-based models have…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Dejia Xu , Ye Yuan , Morteza Mardani , Sifei Liu , Jiaming Song , Zhangyang Wang , Arash Vahdat

Although 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it still faces challenges such as aliasing, projection artifacts, and view inconsistencies, primarily due to the simplification of treating splats as 2D entities.…

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 large generative models and real-time neural rendering using point-based techniques pave the way for a future of widespread visual data distribution through sharing synthesized 3D assets. However, while standardized…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Chenxin Li , Hengyu Liu , Zhiwen Fan , Wuyang Li , Yifan Liu , Panwang Pan , Yixuan Yuan

Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussian Splatting (3DGS), where scenes are represented by a series…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Lanqing Guo , Yufei Wang , Hezhen Hu , Yan Zheng , Yeying Jin , Siyu Huang , Zhangyang Wang

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh