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Related papers: Optimized Minimal 4D Gaussian Splatting

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Reconstructing and predicting dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. Recent physics-informed Gaussian Splatting methods achieve impressive future frame extrapolation but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Denis Gridusov , Maxim Popov , Sergey Kolyubin

Outdoor scene reconstruction remains challenging due to the stark contrast between well-textured, nearby regions and distant backgrounds dominated by low detail, uneven illumination, and sky effects. We introduce a two-stage Gaussian…

Graphics · Computer Science 2025-10-13 Deborah Pintani , Ariel Caputo , Noah Lewis , Marc Stamminger , Fabio Pellacini , Andrea Giachetti

In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly focus on exploring strong geometry regularization. Instead,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Lue Fan , Yuxue Yang , Minxing Li , Hongsheng Li , Zhaoxiang Zhang

Traditional volumetric fusion algorithms preserve the spatial structure of 3D scenes, which is beneficial for many tasks in computer vision and robotics. However, they often lack realism in terms of visualization. Emerging 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Jiaxin Wei , Stefan Leutenegger

Recently, Gaussian Splatting methods have emerged as a desirable substitute for prior Radiance Field methods for novel-view synthesis of scenes captured with multi-view images or videos. In this work, we propose a novel extension to 4D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Karly Hou , Wanhua Li , Hanspeter Pfister

Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following the pioneering work of 3D-GS, several methods have attempted…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Evangelos Ververas , Rolandos Alexandros Potamias , Jifei Song , Jiankang Deng , Stefanos Zafeiriou

We have recently seen great progress in 3D scene reconstruction through explicit point-based 3D Gaussian Splatting (3DGS), notable for its high quality and fast rendering speed. However, reconstructing dynamic scenes such as complex human…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Chao Zhang , Yifeng Zhou , Shuheng Wang , Wenfa Li , Degang Wang , Yi Xu , Shaohui Jiao

Generating synthetic images is a useful method for cheaply obtaining labeled data for training computer vision models. However, obtaining accurate 3D models of relevant objects is necessary, and the resulting images often have a gap in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Bram Vanherle , Brent Zoomers , Jeroen Put , Frank Van Reeth , Nick Michiels

Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiaqi Lin , Zhihao Li , Xiao Tang , Jianzhuang Liu , Shiyong Liu , Jiayue Liu , Yangdi Lu , Xiaofei Wu , Songcen Xu , Youliang Yan , Wenming Yang

3D reconstruction from unconstrained image collections presents substantial challenges due to varying appearances and transient occlusions. In this paper, we introduce Micro-macro Wavelet-based Gaussian Splatting (MW-GS), a novel approach…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yihui Li , Chengxin Lv , Hongyu Yang , Di Huang

Gaussian Splatting (GS) has significantly elevated scene reconstruction efficiency and novel view synthesis (NVS) accuracy compared to Neural Radiance Fields (NeRF), particularly for dynamic scenes. However, current 4D NVS methods, whether…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Fang Li , Hao Zhang , Narendra Ahuja

In this work, we present a novel level-of-detail (LOD) method for 3D Gaussian Splatting that enables real-time rendering of large-scale scenes on memory-constrained devices. Our approach introduces a hierarchical LOD representation that…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Jonas Kulhanek , Marie-Julie Rakotosaona , Fabian Manhardt , Christina Tsalicoglou , Michael Niemeyer , Torsten Sattler , Songyou Peng , Federico Tombari

Modeling dynamic 3D scenes is challenging due to their high-dimensional nature, which requires aggregating information from multiple views to reconstruct time-evolving 3D geometry and motion. We present a novel multi-video 4D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yonghan Lee , Tsung-Wei Huang , Shiv Gehlot , Jaehoon Choi , Guan-Ming Su , Dinesh Manocha

Modeling, understanding, and reconstructing the real world are crucial in XR/VR. Recently, 3D Gaussian Splatting (3D-GS) methods have shown remarkable success in modeling and understanding 3D scenes. Similarly, various 4D representations…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Shengxiang Ji , Guanjun Wu , Jiemin Fang , Jiazhong Cen , Taoran Yi , Wenyu Liu , Qi Tian , Xinggang Wang

Recent progress in pre-trained diffusion models and 3D generation have spurred interest in 4D content creation. However, achieving high-fidelity 4D generation with spatial-temporal consistency remains a challenge. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yifei Zeng , Yanqin Jiang , Siyu Zhu , Yuanxun Lu , Youtian Lin , Hao Zhu , Weiming Hu , Xun Cao , Yao Yao

Immersive video offers a 6-Dof-free viewing experience, potentially playing a key role in future video technology. Recently, 4D Gaussian Splatting has gained attention as an effective approach for immersive video due to its high rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Hao Li , Sicheng Li , Xiang Gao , Abudouaihati Batuer , Lu Yu , Yiyi Liao

Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3D Gaussian Splatting (3DGS) with SLAM to achieve both robust camera pose estimation and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Yunsong Wang , Gim Hee Lee

Decomposing geometry, materials and lighting from a set of images, namely inverse rendering, has been a long-standing problem in computer vision and graphics. Recent advances in neural rendering enable photo-realistic and plausible inverse…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Silong Yong , Venkata Nagarjun Pudureddiyur Manivannan , Bernhard Kerbl , Zifu Wan , Simon Stepputtis , Katia Sycara , Yaqi Xie

Rendering complex reflection of real-world scenes using 3D Gaussian splatting has been a quite promising solution for photorealistic novel view synthesis, but still faces bottlenecks especially in rendering speed and memory storage. This…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Chang Liu , Hongliang Yuan , Lianghao Zhang , Sichao Wang , Jianwei Guo , Shi-Sheng Huang

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao
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