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High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated the ability to model temporal dynamics, it couples Gaussian motion and geometric attributes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yi Zhang , Yulei Kang , Jiangxin Sun , Beihao Xia , Jisheng Dang , Jian-Fang Hu

Novel view synthesis has long been a practical but challenging task, although the introduction of numerous methods to solve this problem, even combining advanced representations like 3D Gaussian Splatting, they still struggle to recover…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Jiahao Wu , Rui Peng , Zhiyan Wang , Lu Xiao , Luyang Tang , Jinbo Yan , Kaiqiang Xiong , Ronggang Wang

The 3D Gaussian Splatting (3D-GS) is a novel method for scene representation and view synthesis. Although Scaffold-GS achieves higher quality real-time rendering compared to the original 3D-GS, its fine-grained rendering of the scene is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Chenyang Xu , XingGuo Deng , Rui Zhong

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 present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representation, unifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hidenobu Matsuki , Riku Murai , Paul H. J. Kelly , Andrew J. Davison

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

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

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Simultaneous Localization and Mapping (SLAM) is pivotal in robotics, with photorealistic scene reconstruction emerging as a key challenge. To address this, we introduce Computational Alignment for Real-Time Gaussian Splatting SLAM (CaRtGS),…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Dapeng Feng , Zhiqiang Chen , Yizhen Yin , Shipeng Zhong , Yuhua Qi , Hongbo Chen

Robot-assisted minimally invasive surgery benefits from enhancing dynamic scene reconstruction, as it improves surgical outcomes. While Neural Radiance Fields (NeRF) have been effective in scene reconstruction, their slow inference speeds…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Haoyu Zhao , Xingyue Zhao , Lingting Zhu , Weixi Zheng , Yongchao Xu

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

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

Generating high-quality novel view renderings of 3D Gaussian Splatting (3DGS) in scenes featuring transient objects is challenging. We propose a novel hybrid representation, termed as HybridGS, using 2D Gaussians for transient objects per…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Jingyu Lin , Jiaqi Gu , Lubin Fan , Bojian Wu , Yujing Lou , Renjie Chen , Ligang Liu , Jieping Ye

Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yunzhou Song , Heguang Lin , Jiahui Lei , Lingjie Liu , Kostas Daniilidis

Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often leads to motion blur, hindering the effectiveness of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jiyuan Zhang , Kang Chen , Shiyan Chen , Yajing Zheng , Tiejun Huang , Zhaofei Yu

3D Gaussian Splatting (3DGS) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates temporally deformable primitives with learnable latent embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mufan Liu , Qi Yang , He Huang , Wenjie Huang , Zhenlong Yuan , Zhu Li , Yiling Xu

The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Huapeng Li , Wenxuan Song , Tianao Xu , Alexandre Elsig , Jonas Kulhanek

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

Dynamic reconstruction of deformable tissues in endoscopic video is a key technology for robot-assisted surgery. Recent reconstruction methods based on neural radiance fields (NeRFs) have achieved remarkable results in the reconstruction of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Weixing Xie , Junfeng Yao , Xianpeng Cao , Qiqin Lin , Zerui Tang , Xiao Dong , Xiaohu Guo

3D Gaussian Splatting (3DGS) achieves impressive quality and rendering speed, but with millions of 3D Gaussians and significant storage and transmission costs. In this paper, we aim to develop a simple yet effective method called NeuralGS…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Zhenyu Tang , Chaoran Feng , Xinhua Cheng , Wangbo Yu , Junwu Zhang , Yuan Liu , Xiaoxiao Long , Wenping Wang , Li Yuan
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