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Related papers: SIMSplat: Predictive Driving Scene Editing with La…

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We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without altering their main details, all in a matter of minutes on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Francesco Palandra , Andrea Sanchietti , Daniele Baieri , Emanuele Rodolà

This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection…

Graphics · Computer Science 2025-10-01 Zhenyu Shu , Junlong Yu , Kai Chao , Shiqing Xin , Ligang Liu

Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hannah Schieber , Jacob Young , Tobias Langlotz , Stefanie Zollmann , Daniel Roth

We propose GGS, a Generalizable Gaussian Splatting method for Autonomous Driving which can achieve realistic rendering under large viewpoint changes. Previous generalizable 3D gaussian splatting methods are limited to rendering novel views…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Huasong Han , Kaixuan Zhou , Xiaoxiao Long , Yusen Wang , Chunxia Xiao

We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS and edits them by using a pre-trained 2D diffusion model…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jing Wu , Jia-Wang Bian , Xinghui Li , Guangrun Wang , Ian Reid , Philip Torr , Victor Adrian Prisacariu

State-of-the-art approaches for conditional human body rendering via Gaussian splatting typically focus on simple body motions captured from many views. This is often in the context of dancing or walking. However, for more complex use…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Maksym Ivashechkin , Oscar Mendez , Richard Bowden

We introduce Dr. Splat, a novel approach for open-vocabulary 3D scene understanding leveraging 3D Gaussian Splatting. Unlike existing language-embedded 3DGS methods, which rely on a rendering process, our method directly associates…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Kim Jun-Seong , GeonU Kim , Kim Yu-Ji , Yu-Chiang Frank Wang , Jaesung Choe , Tae-Hyun Oh

Egocentric scenes exhibit frequent occlusions, varied viewpoints, and dynamic interactions compared to typical scene understanding tasks. Occlusions and varied viewpoints can lead to multi-view semantic inconsistencies, while dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Di Li , Jie Feng , Jiahao Chen , Weisheng Dong , Guanbin Li , Guangming Shi , Licheng Jiao

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

Modern Gaussian Splatting methods have proven highly effective for real-time photorealistic rendering of 3D scenes. However, integrating semantic information into this representation remains a significant challenge, especially in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Roman Titkov , Egor Zubkov , Dmitry Yudin , Jaafar Mahmoud , Malik Mohrat , Gennady Sidorov

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie

Simultaneous Localization and Mapping (SLAM) is one of the most important environment-perception and navigation algorithms for computer vision, robotics, and autonomous cars/drones. Hence, high quality and fast mapping becomes a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Runfa Blark Li , Mahdi Shaghaghi , Keito Suzuki , Xinshuang Liu , Varun Moparthi , Bang Du , Walker Curtis , Martin Renschler , Ki Myung Brian Lee , Nikolay Atanasov , Truong Nguyen

Holistic 3D scene understanding, which jointly models geometry, appearance, and semantics, is crucial for applications like augmented reality and robotic interaction. Existing feed-forward 3D scene understanding methods (e.g., LSM) are…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Qijing Li , Jingxiang Sun , Liang An , Zhaoqi Su , Hongwen Zhang , Yebin Liu

We propose ActiveSplat, an autonomous high-fidelity reconstruction system leveraging Gaussian splatting. Taking advantage of efficient and realistic rendering, the system establishes a unified framework for online mapping, viewpoint…

Robotics · Computer Science 2025-06-17 Yuetao Li , Zijia Kuang , Ting Li , Qun Hao , Zike Yan , Guyue Zhou , Shaohui Zhang

Photorealistic 3D scene reconstruction plays an important role in autonomous driving, enabling the generation of novel data from existing datasets to simulate safety-critical scenarios and expand training data without additional acquisition…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Pou-Chun Kung , Xianling Zhang , Katherine A. Skinner , Nikita Jaipuria

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

High-Fidelity 3D scene reconstruction plays a crucial role in autonomous driving by enabling novel data generation from existing datasets. This allows simulating safety-critical scenarios and augmenting training datasets without incurring…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Pou-Chun Kung , Skanda Harisha , Ram Vasudevan , Aline Eid , Katherine A. Skinner

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Generating realistic 3D scenes from text is crucial for immersive applications like VR, AR, and gaming. While text-driven approaches promise efficiency, existing methods suffer from limited 3D-text data and inconsistent multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Xin Zhang , Shen Chen , Jiale Zhou , Lei Li

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi