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Related papers: i-PhysGaussian: Implicit Physical Simulation for 3…

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3D Gaussian Splatting (3DGS) enables photorealistic rendering but suffers from artefacts due to sparse Structure-from-Motion (SfM) initialisation. To address this limitation, we propose GP-GS, a Gaussian Process (GP) based densification…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhihao Guo , Jingxuan Su , Chenghao Qian , Shenglin Wang , Jinlong Fan , Jing Zhang , Wei Zhou , Hadi Amirpour , Yunlong Zhao , Liangxiu Han , Peng Wang

This paper studies the problem of estimating physical properties (system identification) through visual observations. To facilitate geometry-aware guidance in physical property estimation, we introduce a novel hybrid framework that…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Junhao Cai , Yuji Yang , Weihao Yuan , Yisheng He , Zilong Dong , Liefeng Bo , Hui Cheng , Qifeng Chen

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

3D Gaussian Splats (3DGS) have proven a versatile rendering primitive, both for inverse rendering as well as real-time exploration of scenes. In these applications, coherence across camera frames and multiple views is crucial, be it for…

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

We present GP-4DGS, a novel framework that integrates Gaussian Processes (GPs) into 4D Gaussian Splatting (4DGS) for principled probabilistic modeling of dynamic scenes. While existing 4DGS methods focus on deterministic reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Mijeong Kim , Jungtaek Kim , Bohyung Han

Simultaneous localization and mapping is essential for position tracking and scene understanding. 3D Gaussian-based map representations enable photorealistic reconstruction and real-time rendering of scenes using multiple posed cameras. We…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Lisong C. Sun , Neel P. Bhatt , Jonathan C. Liu , Zhiwen Fan , Zhangyang Wang , Todd E. Humphreys , Ufuk Topcu

3D Gaussian Splatting (3DGS) has emerged as a core technique for 3D representation. Its effectiveness largely depends on precise camera poses and accurate point cloud initialization, which are often derived from pretrained Multi-View Stereo…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Chong Cheng , Zijian Wang , Sicheng Yu , Yu Hu , Nanjie Yao , Hao Wang

3D Gaussian Splatting (3DGS) has emerged as a promising 3D reconstruction technique. The traditional 3DGS training pipeline follows three sequential steps: Gaussian densification, Gaussian projection, and color splatting. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junyi Wu , Jiaming Xu , Jinhao Li , Yongkang Zhou , Jiayi Pan , Xingyang Li , Guohao Dai

While 3D Gaussian Splatting (3DGS) enables real-time rendering, its training demands workstation-level compute and memory, making mobile deployment impractical under minute-scale time budgets and limited peak memory. We present PocketGS, a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Wenzhi Guo , Guangchi Fang , Shu Yang , Bing Wang

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

While 3D Gaussian Splatting (3DGS) has revolutionized photorealistic rendering, its vast ecosystem of assets remains incompatible with high-performance LiDAR simulation, a critical tool for robotics and autonomous driving. We present…

Robotics · Computer Science 2025-09-23 Junzhe Wu , Yufei Jia , Yiyi Yan , Zhixing Chen , Tiao Tan , Zifan Wang , Guangyu Wang

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

The accurate 3D reconstruction of deformable soft body tissues from endoscopic videos is a pivotal challenge in medical applications such as VR surgery and medical image analysis. Existing methods often struggle with accuracy and the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yangsen Chen , Hao Wang

Physical adversarial attack methods expose the vulnerabilities of deep neural networks and pose a significant threat to safety-critical scenarios such as autonomous driving. Camouflage-based physical attack is a more promising approach…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Tianrui Lou , Xiaojun Jia , Siyuan Liang , Jiawei Liang , Ming Zhang , Yanjun Xiao , Xiaochun Cao

3D Gaussian Splatting has advanced radiance field reconstruction, enabling high-quality view synthesis and fast rendering in 3D modeling. While adversarial attacks on object detection models are well-studied for 2D images, their impact on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Abdurrahman Zeybey , Mehmet Ergezer , Tommy Nguyen

Recently, significant advancements have been made in the reconstruction and generation of 3D assets, including static cases and those with physical interactions. To recover the physical properties of 3D assets, existing methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Yuchen Lin , Chenguo Lin , Jianjin Xu , Yadong Mu

As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dynamic scene. However, previous works fail to accurately…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Jeongmin Bae , Seoha Kim , Youngsik Yun , Hahyun Lee , Gun Bang , Youngjung Uh