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Related papers: CoGS: Controllable Gaussian Splatting

200 papers

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yujie Wang , Praneeth Chakravarthula , Baoquan Chen

3D Gaussian Splatting (3DGS) demonstrates unparalleled superior performance in 3D scene reconstruction. However, 3DGS heavily relies on the sharp images. Fulfilling this requirement can be challenging in real-world scenarios especially when…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Yijia Guo , Liwen Hu , Yuanxi Bai , Jiawei Yao , Lei Ma , Tiejun Huang

3D Gaussian Splatting (3DGS) has gained significant attention for their high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Sangyoun Lee

In this work, we propose a novel method to supervise 3D Gaussian Splatting (3DGS) scenes using optical tactile sensors. Optical tactile sensors have become widespread in their use in robotics for manipulation and object representation;…

Robotics · Computer Science 2024-08-19 Aiden Swann , Matthew Strong , Won Kyung Do , Gadiel Sznaier Camps , Mac Schwager , Monroe Kennedy

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

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Saptarshi Neil Sinha , Holger Graf , Michael Weinmann

3D Gaussian Splatting (3DGS) has gained significant attention due to its high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Wonjoon Lee , Taeoh Kim , Dongyoon Wee , Sangyoun Lee

This paper considers the problem of modeling articulated objects captured in 2D videos to enable novel view synthesis, while also being easily editable, drivable, and re-posable. To tackle this challenging problem, we propose RigGS, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yuxin Yao , Zhi Deng , Junhui Hou

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

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

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this constraint, multiple efforts have been made to train Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yang Fu , Sifei Liu , Amey Kulkarni , Jan Kautz , Alexei A. Efros , Xiaolong Wang

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yiming Huang , Beilei Cui , Long Bai , Ziqi Guo , Mengya Xu , Mobarakol Islam , Hongliang Ren

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Real2Sim is becoming increasingly important with the rapid development of surgical artificial intelligence (AI) and autonomy. In this work, we propose a novel Real2Sim methodology, Instrument-Splatting, that leverages 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Shuojue Yang , Zijian Wu , Mingxuan Hong , Qian Li , Daiyun Shen , Septimiu E. Salcudean , Yueming Jin

3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Shen Chen , Jiale Zhou , Lei Li

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an assumption that is often violated in real-world applications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhankuo Xu , Chaoran Feng , Yingtao Li , Jianbin Zhao , Jiashu Yang , Wangbo Yu , Li Yuan , Yonghong Tian

The field of 3D reconstruction from images has rapidly evolved in the past few years, first with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian Splatting (3DGS). The latter provides a significant edge…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Avinash Paliwal , Wei Ye , Jinhui Xiong , Dmytro Kotovenko , Rakesh Ranjan , Vikas Chandra , Nima Khademi Kalantari

Surgical reconstruction of dynamic tissues from endoscopic videos is a crucial technology in robot-assisted surgery. The development of Neural Radiance Fields (NeRFs) has greatly advanced deformable tissue reconstruction, achieving…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Wenfeng Huang , Xiangyun Liao , Yinling Qian , Hao Liu , Yongming Yang , Wenjing Jia , Qiong Wang

Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Keng-Wei Chang , Zi-Ming Wang , Shang-Hong Lai

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull
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