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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

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to efficiently and stably achieve high-quality geometric fidelity remains a core challenge. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kehua Chen , Tianlu Mao , Xinzhu Ma , Hao Jiang , Zehao Li , Zihan Liu , Shuqin Gao , Honglong Zhao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

We present DC-Gaussian, a new method for generating novel views from in-vehicle dash cam videos. While neural rendering techniques have made significant strides in driving scenarios, existing methods are primarily designed for videos…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Linhan Wang , Kai Cheng , Shuo Lei , Shengkun Wang , Wei Yin , Chenyang Lei , Xiaoxiao Long , Chang-Tien Lu

We introduce Gaussian-Flow, a novel point-based approach for fast dynamic scene reconstruction and real-time rendering from both multi-view and monocular videos. In contrast to the prevalent NeRF-based approaches hampered by slow training…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Youtian Lin , Zuozhuo Dai , Siyu Zhu , Yao Yao

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scenarios. However, the prerequisite for modeling dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hengyu Liu , Yifan Liu , Chenxin Li , Wuyang Li , Yixuan Yuan

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

In this paper, we propose a 3D geometry-aware deformable Gaussian Splatting method for dynamic view synthesis. Existing neural radiance fields (NeRF) based solutions learn the deformation in an implicit manner, which cannot incorporate 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Zhicheng Lu , Xiang Guo , Le Hui , Tianrui Chen , Min Yang , Xiao Tang , Feng Zhu , Yuchao Dai

Tissue deformation poses a key challenge for accurate surgical scene reconstruction. Despite yielding high reconstruction quality, existing methods suffer from slow rendering speeds and long training times, limiting their intraoperative…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Shuojue Yang , Qian Li , Daiyun Shen , Bingchen Gong , Qi Dou , Yueming Jin

3D Gaussian Splatting techniques have enabled efficient photo-realistic rendering of static scenes. Recent works have extended these approaches to support surface reconstruction and tracking. However, tracking dynamic surfaces with 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Chengwei Zheng , Lixin Xue , Juan Zarate , Jie Song

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

Recent developments in 3D reconstruction and neural rendering have significantly propelled the capabilities of photo-realistic 3D scene rendering across various academic and industrial fields. The 3D Gaussian Splatting technique, alongside…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zexu Huang , Min Xu , Stuart Perry

Reconstructing large-scale dynamic driving scenes remains challenging due to the coexistence of static environments with extreme depth variation and diverse dynamic actors exhibiting complex motions. Existing Gaussian Splatting based…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Cong Wang , Ruiqi Song , Wei Tian , Chenming Zhang , Lingxi Li , Long Chen

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

Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustly filters out transient distractors during 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Alexander Markin , Vadim Pryadilshchikov , Artem Komarichev , Ruslan Rakhimov , Peter Wonka , Evgeny Burnaev

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

Although significant progress has been made in reconstructing sharp 3D scenes from motion-blurred images, a transition to real-world applications remains challenging. The primary obstacle stems from the severe blur which leads to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Jeongtaek Oh , Jaeyoung Chung , Dongwoo Lee , Kyoung Mu Lee

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman