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Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, such optimization is prone to overfitting, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Meiying Gu , Jiawei Zhang , Jiahe Li , Xiaohan Yu , Haonan Luo , Jin Zheng , Xiao Bai

We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially and progressively model the static background of the entire…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Xiaoyu Zhou , Zhiwei Lin , Xiaojun Shan , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

Monocular object pose estimation, as a pivotal task in computer vision and robotics, heavily depends on accurate 2D-3D correspondences, which often demand costly CAD models that may not be readily available. Object 3D reconstruction methods…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Luqing Luo , Shichu Sun , Jiangang Yang , Linfang Zheng , Jinwei Du , Jian Liu

Surface reconstruction and novel view rendering from sparse-view images are challenging. Signed Distance Function (SDF)-based methods struggle with fine details, while 3D Gaussian Splatting (3DGS)-based approaches lack global geometry…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Zihui Gao , Jia-Wang Bian , Guosheng Lin , Hao Chen , Chunhua Shen

This paper looks into the problem of grasping unknown objects in a cluttered environment using 3D point cloud data obtained from a range or an RGBD sensor. The objective is to identify graspable regions and detect suitable grasp poses from…

Robotics · Computer Science 2018-07-30 Olyvia Kundu , Swagat Kumar

The aesthetic quality of a scene depends strongly on camera viewpoint. Existing approaches for aesthetic viewpoint suggestion are either single-view adjustments, predicting limited camera adjustments from a single image without…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheyang Tang , Armin Shafiee Sarvestani , Jialu Xu , Xiaoyu Xu , Zhou Wang

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

3D Gaussian Splatting (3DGS) has recently emerged as a powerful scene representation and is increasingly used for visual localization and pose refinement. However, despite its high-quality differentiable rendering, the robustness of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Mangyu Kong , Jaewon Lee , Seongwon Lee , Euntai Kim

Human has an incredible ability to effortlessly perceive the viewpoint difference between two images containing the same object, even when the viewpoint change is astonishingly vast with no co-visible regions in the images. This remarkable…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Yujing Sun , Caiyi Sun , Yuan Liu , Yuexin Ma , Siu Ming Yiu

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

Corner cases are crucial for training and validating autonomous driving systems, yet collecting them from the real world is often costly and hazardous. Editing objects within captured sensor data offers an effective alternative for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Jiusi Li , Jackson Jiang , Jinyu Miao , Miao Long , Tuopu Wen , Peijin Jia , Shengxiang Liu , Chunlei Yu , Maolin Liu , Yuzhan Cai , Kun Jiang , Mengmeng Yang , Diange Yang

In this paper, we propose a novel method for joint recovery of camera pose, object geometry and spatially-varying Bidirectional Reflectance Distribution Function (svBRDF) of 3D scenes that exceed object-scale and hence cannot be captured…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Carolin Schmitt , Božidar Antić , Andrei Neculai , Joo Ho Lee , Andreas Geiger

Reconstructing intricate, ever-changing environments remains a central ambition in computer vision, yet existing solutions often crumble before the complexity of real-world dynamics. We present DynaSplat, an approach that extends Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Junli Deng , Ping Shi , Qipei Li , Jinyang Guo

Scene representations using 3D Gaussian primitives have produced excellent results in modeling the appearance of static and dynamic 3D scenes. Many graphics applications, however, demand the ability to manipulate both the appearance and the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Ri-Zhao Qiu , Ge Yang , Weijia Zeng , Xiaolong Wang

Motion segmentation in dynamic scenes is highly challenging, as conventional methods heavily rely on estimating camera poses and point correspondences from inherently noisy motion cues. Existing statistical inference or iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Xiankang He , Peile Lin , Ying Cui , Dongyan Guo , Chunhua Shen , Xiaoqin Zhang

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Shuai Du , Youyi Zheng

Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment. Large-scale scenes and critical camera motions are great challenges facing the research community to…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Qi Cai , Lilian Zhang , Yuanxin Wu , Wenxian Yu , Dewen Hu

3D Gaussian Splatting (3DGS) is a major breakthrough in 3D scene reconstruction. With a number of views of a given object or scene, the algorithm trains a model composed of 3D gaussians, which enables the production of novel views from…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Matthieu Gendrin , Stéphane Pateux , Théo Ladune