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3D Gaussian Splatting (3DGS) is a recent approach for scene rendering. Although primarily designed for view synthesis, its potential for scene understanding tasks remains underexplored. In this work, we conduct a comparative evaluation of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Julia Farganus , Krzysztof Żurawicki , Arkadiusz Gaweł , Weronika Jakubowska , Halina Kwaśnicka

As generative models become increasingly capable of producing high-fidelity visual content, the demand for efficient, interpretable, and editable image representations has grown substantially. Recent advances in 2D Gaussian Splatting (2DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Hao Wang , Ashish Bastola , Chaoyi Zhou , Wenhui Zhu , Xiwen Chen , Xuanzhao Dong , Siyu Huang , Abolfazl Razi

We introduce an image upscaling technique tailored for 3D Gaussian Splatting (3DGS) on lightweight GPUs. Compared to 3DGS, it achieves significantly higher rendering speeds and reduces artifacts commonly observed in 3DGS reconstructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Simon Niedermayr , Christoph Neuhauser Rüdiger Westermann

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie

Sparse-view scene reconstruction often faces significant challenges due to the constraints imposed by limited observational data. These limitations result in incomplete information, leading to suboptimal reconstructions using existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xiangyu Sun , Runnan Chen , Mingming Gong , Dong Xu , Tongliang Liu

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

3D reconstruction of indoor and urban environments is a prominent research topic with various downstream applications. However, existing geometric priors for addressing low-texture regions in indoor and urban settings often lack global…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Xiyu Zhang , Chong Bao , Yipeng Chen , Hongjia Zhai , Yitong Dong , Hujun Bao , Zhaopeng Cui , Guofeng Zhang

3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purpose and not tailored to the structure of the problem. In…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Naama Pearl , Stefano Esposito , Haofei Xu , Amit Peleg , Patricia Gschossmann , Lorenzo Porzi , Peter Kontschieder , Gerard Pons-Moll , Andreas Geiger

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

In this study, we present an end-to-end pipeline capable of converting drone-captured video streams into high-fidelity 3D reconstructions with minimal latency. Unmanned aerial vehicles (UAVs) are extensively used in aerial real-time…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Christos Maikos , Georgios Angelidis , Georgios Th. Papadopoulos

3D Gaussian splatting (3DGS) has demonstrated impressive performance in synthesizing high-fidelity novel views. Nonetheless, its effectiveness critically depends on the quality of the initialized point cloud. Specifically, achieving uniform…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yikang Zhang , Rui Fan

Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, such optimization is prone to overfitting, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Meiying Gu , Jiawei Zhang , Jiahe Li , Xiaohan Yu , Haonan Luo , Jin Zheng , Xiao Bai

Generalizable 3D Gaussian Splatting aims to directly predict Gaussian parameters using a feed-forward network for scene reconstruction. Among these parameters, Gaussian means are particularly difficult to predict, so depth is usually…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Wei Long , Haifeng Wu , Shiyin Jiang , Jinhua Zhang , Xinchun Ji , Shuhang Gu

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangsen Chen , Hao Wang

Recent advances in generalizable 3D Gaussian Splatting have demonstrated promising results in real-time high-fidelity rendering without per-scene optimization, yet existing approaches still struggle to handle unfamiliar visual content…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Yifan Liu , Keyu Fan , Weihao Yu , Chenxin Li , Hao Lu , Yixuan Yuan

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Haoxuan Qu , Yujun Cai , Hossein Rahmani , Ajay Kumar , Junsong Yuan , Jun Liu

In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances…

Robotics · Computer Science 2024-10-10 Zijun Xu , Rui Jin , Ke Wu , Yi Zhao , Zhiwei Zhang , Jieru Zhao , Fei Gao , Zhongxue Gan , Wenchao Ding

Accurately reconstructing a 3D scene including explicit geometry information is both attractive and challenging. Geometry reconstruction can benefit from incorporating differentiable appearance models, such as Neural Radiance Fields and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Ancheng Lin , Yusheng Xiang , Paul Kennedy , Jun Li

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon