English
Related papers

Related papers: Instruct-4DGS: Efficient Dynamic Scene Editing via…

200 papers

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of text-to-4D dynamic 3D scene generation with diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yufeng Zheng , Xueting Li , Koki Nagano , Sifei Liu , Karsten Kreis , Otmar Hilliges , Shalini De Mello

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differentiable 3D Gaussians. However, its rendering speed and model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Alex Hanson , Allen Tu , Geng Lin , Vasu Singla , Matthias Zwicker , Tom Goldstein

Surgical scene simulation plays a crucial role in surgical education and simulator-based robot learning. Traditional approaches for creating these environments with surgical scene involve a labor-intensive process where designers hand-craft…

Robotics · Computer Science 2024-08-07 Zhenya Yang , Kai Chen , Yonghao Long , Qi Dou

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Bernhard Kerbl , Andréas Meuleman , Georgios Kopanas , Michael Wimmer , Alexandre Lanvin , George Drettakis

Real-time, high-fidelity reconstruction of dynamic driving scenes is challenged by complex dynamics and sparse views, with prior methods struggling to balance quality and efficiency. We propose DrivingScene, an online, feed-forward…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Qirui Hou , Wenzhang Sun , Chang Zeng , Chunfeng Wang , Hao Li , Jianxun Cui

Autonomous driving needs fast, scalable 4D reconstruction and re-simulation for training and evaluation, yet most methods for dynamic driving scenes still rely on per-scene optimization, known camera calibration, or short frame windows,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Xiaoxue Chen , Ziyi Xiong , Yuantao Chen , Gen Li , Nan Wang , Hongcheng Luo , Long Chen , Haiyang Sun , Bing Wang , Guang Chen , Hangjun Ye , Hongyang Li , Ya-Qin Zhang , Hao Zhao

Recently, 3D Gaussian splatting (3D-GS) has gained popularity in novel-view scene synthesis. It addresses the challenges of lengthy training times and slow rendering speeds associated with Neural Radiance Fields (NeRFs). Through rapid,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Sharath Girish , Kamal Gupta , Abhinav Shrivastava

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

Constructing photo-realistic Free-Viewpoint Videos (FVVs) of dynamic scenes from multi-view videos remains a challenging endeavor. Despite the remarkable advancements achieved by current neural rendering techniques, these methods generally…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Jiakai Sun , Han Jiao , Guangyuan Li , Zhanjie Zhang , Lei Zhao , Wei Xing

Existing 4D Gaussian Splatting (4DGS) methods struggle to accurately reconstruct dynamic scenes, often failing to resolve ambiguous pixel correspondences and inadequate densification in dynamic regions. We address these issues by…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Taeho Kang , Jaeyeon Park , Kyungjin Lee , Youngki Lee

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

Recently many techniques have emerged to create high quality 3D assets and scenes. When it comes to editing of these objects, however, existing approaches are either slow, compromise on quality, or do not provide enough customization. We…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Vishnu Jaganathan , Hannah Hanyun Huang , Muhammad Zubair Irshad , Varun Jampani , Amit Raj , Zsolt Kira

We introduce StyleGaussian, a novel 3D style transfer technique that allows instant transfer of any image's style to a 3D scene at 10 frames per second (fps). Leveraging 3D Gaussian Splatting (3DGS), StyleGaussian achieves style transfer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Kunhao Liu , Fangneng Zhan , Muyu Xu , Christian Theobalt , Ling Shao , Shijian Lu

Neural Radiance Fields achieve high-fidelity scene representation but suffer from costly training and rendering, while 3D Gaussian splatting offers real-time performance with strong empirical results. Recently, solutions that harness the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Grzegorz Wilczyński , Mikołaj Zieliński , Krzysztof Byrski , Joanna Waczyńska , Dominik Belter , Przemysław Spurek

Despite recent advances in single-object front-facing inpainting using NeRF and 3D Gaussian Splatting (3DGS), inpainting in complex 360{\deg} scenes remains largely underexplored. This is primarily due to three key challenges: (i)…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Shaoxiang Wang , Shihong Zhang , Christen Millerdurai , Rüdiger Westermann , Didier Stricker , Alain Pagani

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

The efficient rendering and explicit nature of 3DGS promote the advancement of 3D scene manipulation. However, existing methods typically encounter challenges in controlling the manipulation region and are unable to furnish the user with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Yian Zhao , Wanshi Xu , Ruochong Zheng , Pengchong Qiao , Chang Liu , Jie Chen

Efficient scene representations are essential for many real-world applications, especially those involving spatial measurement. Although current NeRF-based methods have achieved impressive results in reconstructing building-scale scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jianlin Guo , Haihong Xiao , Wenxiong Kang

The recent Gaussian Splatting achieves high-quality and real-time novel-view synthesis of the 3D scenes. However, it is solely concentrated on the appearance and geometry modeling, while lacking in fine-grained object-level scene…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Mingqiao Ye , Martin Danelljan , Fisher Yu , Lei Ke

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance significantly degrades in dynamic environments. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Ying Zang , Xuanyi Liu , Yidong Han , Deyi Ji , Chaotao Ding , Yuanqi Hu , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu