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3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis. However, existing methods struggle to adaptively optimize the distribution of Gaussian primitives based on scene characteristics, making it…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Hongbi Zhou , Zhangkai Ni

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 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

Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data. Although 3D Gaussian Splatting (3DGS) has recently demonstrated high-quality results with real-time performance, it still faces…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Haodong Xiang , Xinghui Li , Kai Cheng , Xiansong Lai , Wanting Zhang , Zhichao Liao , Long Zeng , Xueping Liu

Decoupling lighting from geometry using unconstrained photo collections is notoriously challenging. Solving it would benefit many users as creating complex 3D assets takes days of manual labor. Many previous works have attempted to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Joanna Kaleta , Kacper Kania , Tomasz Trzcinski , Marek Kowalski

Professional color editing requires precise control over both color (hue and saturation) and lightness, ideally through separate, independent controls. We present a real-time interactive color editing framework for 3D Gaussian Splatting…

Graphics · Computer Science 2026-04-03 Cheng-Kang Ted Chao , Yotam Gingold

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

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

3D Gaussian Splatting has recently emerged as an efficient solution for high-quality and real-time novel view synthesis. However, its capability for accurate surface reconstruction remains underexplored. Due to the discrete and unstructured…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Qing Li , Huifang Feng , Xun Gong , Yu-Shen Liu

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jonas Kulhanek , Songyou Peng , Zuzana Kukelova , Marc Pollefeys , Torsten Sattler

3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However, current methods require highly controlled environments (no…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Sara Sabour , Lily Goli , George Kopanas , Mark Matthews , Dmitry Lagun , Leonidas Guibas , Alec Jacobson , David J. Fleet , Andrea Tagliasacchi

Implicit Neural Representation for Videos (NeRV) has introduced a novel paradigm for video representation and compression, outperforming traditional codecs. As model size grows, however, slow encoding and decoding speed and high memory…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Inseo Lee , Youngyoon Choi , Joonseok Lee

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Yuanyuan Gao , Yalun Dai , Hao Li , Weicai Ye , Junyi Chen , Danpeng Chen , Dingwen Zhang , Tong He , Guofeng Zhang , Junwei Han

In this paper, we introduce \textbf{GS-SLAM} that first utilizes 3D Gaussian representation in the Simultaneous Localization and Mapping (SLAM) system. It facilitates a better balance between efficiency and accuracy. Compared to recent SLAM…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Chi Yan , Delin Qu , Dan Xu , Bin Zhao , Zhigang Wang , Dong Wang , Xuelong Li

Event cameras, known for their high dynamic range, absence of motion blur, and low energy usage, have recently found a wide range of applications thanks to these attributes. In the past few years, the field of event-based 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Hiroyuki Deguchi , Mana Masuda , Takuya Nakabayashi , Hideo Saito

Recent text-guided generation of individual 3D object has achieved great success using diffusion priors. However, these methods are not suitable for object insertion and replacement tasks as they do not consider the background, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Hanyuan Xiao , Yingshu Chen , Huajian Huang , Haolin Xiong , Jing Yang , Pratusha Prasad , Yajie Zhao

We present MS-Splatting -- a multi-spectral 3D Gaussian Splatting (3DGS) framework that is able to generate multi-view consistent novel views from images of multiple, independent cameras with different spectral domains. In contrast to…

Graphics · Computer Science 2026-02-17 Lukas Meyer , Josef Grün , Maximilian Weiherer , Bernhard Egger , Marc Stamminger , Linus Franke