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Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-Gaussian or voxel-to-Gaussian pipelines that uniformly allocate Gaussians, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Injae Kim , Chaehyeon Kim , Minseong Bae , Minseok Joo , Hyunwoo J. Kim

Creating 4D fields of Gaussian Splatting from images or videos is a challenging task due to its under-constrained nature. While the optimization can draw photometric reference from the input videos or be regulated by generative models,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Quankai Gao , Qiangeng Xu , Zhe Cao , Ben Mildenhall , Wenchao Ma , Le Chen , Danhang Tang , Ulrich Neumann

3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it suffers from a substantial memory footprint, particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Yangming Zhang , Jian Xu , Chaojian Li , Kunxiong Zhu , Wei Niu , Gagan Agrawal , Yang Katie Zhao , Jian Wang , Yingyan Celine Lin , Miao Yin

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

3D Gaussian Splatting demonstrates excellent quality and speed in novel view synthesis. Nevertheless, the huge file size of the 3D Gaussians presents challenges for transmission and storage. Current works design compact models to replace…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Shuzhao Xie , Weixiang Zhang , Chen Tang , Yunpeng Bai , Rongwei Lu , Shijia Ge , Zhi Wang

3D Gaussian Splatting (3DGS) is a new method for modeling and rendering 3D radiance fields that achieves much faster learning and rendering time compared to SOTA NeRF methods. However, it comes with a drawback in the much larger storage…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 KL Navaneet , Kossar Pourahmadi Meibodi , Soroush Abbasi Koohpayegani , Hamed Pirsiavash

3D Gaussian Splatting (3DGS) achieves high-quality novel view synthesis with real-time rendering, but its storage cost remains prohibitive for practical deployment. Existing post-training compression methods still rely on many coupled…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Shuzhao Xie , Junchen Ge , Weixiang Zhang , Jiahang Liu , Chen Tang , Yunpeng Bai , Shijia Ge , Jingyan Jiang , Yuzhi Huang , Fengnian Yang , Cong Zhang , Xiaoyi Fan , Zhi Wang

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D scenes with numerous explicit Gaussian primitives imposes…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Joo Chan Lee , Jong Hwan Ko , Eunbyung Park

Dynamic novel view synthesis (NVS) is essential for creating immersive experiences. Existing approaches have advanced dynamic NVS by introducing 3D Gaussian Splatting (3DGS) with implicit deformation fields or indiscriminately assigned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Kaizhe Zhang , Yijie Zhou , Weizhan Zhang , Caixia Yan , Haipeng Du , yugui xie , Yu-Hui Wen , Yong-Jin Liu

Recent advancements in 3D Gaussian Splatting have enhanced efficient and high-quality novel view synthesis. However, representing scenes requires a large number of Gaussian points, leading to high storage demands and limiting practical…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Liheng Zhang , Weihao Yu , Zubo Lu , Haozhi Gu , Jin Huang

Understanding 4D point cloud videos is essential for enabling intelligent agents to perceive dynamic environments. However, temporal scale bias across varying frame rates and distributional uncertainty in irregular point clouds make it…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Jiayi Tian , Jiaze Wang

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

3D Gaussian Splatting has recently emerged as a highly promising technique for modeling of static 3D scenes. In contrast to Neural Radiance Fields, it utilizes efficient rasterization allowing for very fast rendering at high-quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Wieland Morgenstern , Florian Barthel , Anna Hilsmann , Peter Eisert

Reconstructing 3D vessel structures from sparse-view dynamic digital subtraction angiography (DSA) images enables accurate medical assessment while reducing radiation exposure. Existing methods often produce suboptimal results or require…

Image and Video Processing · Electrical Eng. & Systems 2025-03-27 Zhentao Liu , Ruyi Zha , Huangxuan Zhao , Hongdong Li , Zhiming Cui

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both cases. This work introduces SDD-4DGS, the first framework…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Dai Sun , Huhao Guan , Kun Zhang , Xike Xie , S. Kevin Zhou

Volumetric video represents a transformative advancement in visual media, enabling users to freely navigate immersive virtual experiences and narrowing the gap between digital and real worlds. However, the need for extensive manual…

Graphics · Computer Science 2024-09-16 Yuheng Jiang , Zhehao Shen , Yu Hong , Chengcheng Guo , Yize Wu , Yingliang Zhang , Jingyi Yu , Lan Xu

Recently, immersive media and autonomous driving applications have significantly advanced through 3D Gaussian Splatting (3DGS), which offers high-fidelity rendering and computational efficiency. Despite these advantages, 3DGS as a…

Graphics · Computer Science 2025-05-27 Kangli Wang , Shihao Li , Qianxi Yi , Wei Gao

Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Rui Song , Chenwei Liang , Yan Xia , Walter Zimmer , Hu Cao , Holger Caesar , Andreas Festag , Alois Knoll
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