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Related papers: FLEG: Feed-Forward Language Embedded Gaussian Spla…

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3D Gaussian Splatting (3DGS) has emerged as a powerful representation for neural scene reconstruction, offering high-quality novel view synthesis while maintaining computational efficiency. In this paper, we extend the capabilities of 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Jens Piekenbrinck , Christian Schmidt , Alexander Hermans , Narunas Vaskevicius , Timm Linder , Bastian Leibe

Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semantic predictions across multi-view observations. In this paper, we present OpenGaFF, a novel…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Kunyi Li , Michael Niemeyer , Sen Wang , Stefano Gasperini , Nassir Navab , Federico Tombari

Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally limits their scalability, making high-resolution synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yixing Lao , Xuyang Bai , Xiaoyang Wu , Nuoyuan Yan , Zixin Luo , Tian Fang , Jean-Daniel Nahmias , Yanghai Tsin , Shiwei Li , Hengshuang Zhao

Recent advancements in photo-realistic novel view synthesis have been significantly driven by Gaussian Splatting (3DGS). Nevertheless, the explicit nature of 3DGS data entails considerable storage requirements, highlighting a pressing need…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Minye Wu , Tinne Tuytelaars

Reconstructing large-scale urban scenes from sparse aerial views is a crucial yet challenging task. Due to biased top-down and shallow-oblique camera poses, sparse aerial captures exhibit strong evidence imbalance: roofs and open regions…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Dongli Wu , Zhuoxiao Li , Tongyan Hua , Yinrui Ren , Xiaobao Wei , Rongjun Qin , Wufan Zhao

Feed-forward 3D Gaussian Splatting (3DGS) enables efficient one-pass scene reconstruction, providing 3D representations for novel view synthesis without per-scene optimization. However, existing methods typically predict pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Jongmin Park , Minh-Quan Viet Bui , Juan Luis Gonzalez Bello , Jaeho Moon , Jihyong Oh , Munchurl Kim

Generating a coherent 3D scene representation from multi-view images is a fundamental yet challenging task. Existing methods often struggle with multi-view fusion, leading to fragmented 3D representations and sub-optimal performance. To…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Junho Kim , Seongwon Lee

Feedforward 3D Gaussian Splatting (3DGS) often struggles in trajectory-based sparse-view driving scenes. Existing Gaussian repair methods mainly target optimization-based 3DGS, while diffusion-based repair is typically restricted to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Rui Song , Tianhui Cai , Markus Gross , Xingcheng Zhou , Zewei Zhou , Zhiyu Huang , Olaf Wysocki , Jiaqi Ma

We propose HoliGS, a novel deformable Gaussian splatting framework that addresses embodied view synthesis from long monocular RGB videos. Unlike prior 4D Gaussian splatting and dynamic NeRF pipelines, which struggle with training overhead…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Xiaoyuan Wang , Yizhou Zhao , Botao Ye , Xiaojun Shan , Weijie Lyu , Lu Qi , Kelvin C. K. Chan , Yinxiao Li , Ming-Hsuan Yang

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

Visualization of large-scale time-dependent simulation data is crucial for domain scientists to analyze complex phenomena, but it demands significant I/O bandwidth, storage, and computational resources. To enable effective visualization on…

Graphics · Computer Science 2025-07-18 Siyuan Yao , Chaoli Wang

Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations. They are useful for a wide range of graph analysis tasks including link prediction, node classification, recommendation and…

Machine Learning · Computer Science 2019-12-03 Bhagya Hettige , Yuan-Fang Li , Weiqing Wang , Wray Buntine

The recent development of feedforward 3D Gaussian Splatting (3DGS) presents a new paradigm to reconstruct 3D scenes. Using neural networks trained on large-scale multi-view datasets, it can directly infer 3DGS representations from sparse…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Zetian Song , Jiaye Fu , Jiaqi Zhang , Xiaohan Lu , Chuanmin Jia , Siwei Ma , Wen Gao

Federated learning (FL) offers a promising framework for collaborative digital pathology by enabling model training across institutions. However, real-world deployments face heterogeneity arising from diverse multiple instance learning…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Luru Jing , Cong Cong , Yanyuan Chen , Yongzhi Cao

Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However, it may require a large number of Gaussians, which creates a substantial memory footprint. This paper introduces GES (Generalized…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Abdullah Hamdi , Luke Melas-Kyriazi , Jinjie Mai , Guocheng Qian , Ruoshi Liu , Carl Vondrick , Bernard Ghanem , Andrea Vedaldi

Language-driven 3D Gaussian Splatting (3DGS) editing provides a more convenient approach for modifying complex scenes in VR/AR. Standard pipelines typically adopt a two-stage strategy: first editing multiple 2D views, and then optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yanhui Chen , Jiahong Li , Jingchao Wang , Junyi Lin , Zixin Zeng , Yang Shi

3D Gaussian Splatting (3DGS) achieves an appealing balance between rendering quality and efficiency, but relies on approximating 3D Gaussians as 2D projections--an assumption that degrades accuracy, especially under generic large…

Graphics · Computer Science 2026-03-13 Zixun Huang , Cho-Ying Wu , Yuliang Guo , Xinyu Huang , Liu Ren

Current novel view synthesis methods are typically designed for high-quality and clean input images. However, in foggy scenes, scattering and attenuation can significantly degrade the quality of rendering. Although NeRF-based dehazing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Jinze Yu , Yiqun Wang , Aiheng Jiang , Zhengda Lu , Jianwei Guo , Yong Li , Hongxing Qin , Xiaopeng Zhang

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels