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Recent prominence in 3D Gaussian Splatting (3DGS) has enabled real-time rendering while maintaining high-fidelity novel view synthesis. However, 3DGS resorts to the Gaussian function that is low-pass by nature and is restricted in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Junyu Zhou , Yuyang Huang , Wenrui Dai , Junni Zou , Ziyang Zheng , Nuowen Kan , Chenglin Li , Hongkai Xiong

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

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 (3DGS) has emerged as a leading approach for high-quality novel view synthesis, with numerous variants extending its applicability to a broad spectrum of 3D and 4D scene reconstruction tasks. Despite its success, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiming Wang , Shaofei Wang , Marko Mihajlovic , Siyu Tang

We introduce SPFSplatV2, an efficient feed-forward framework for 3D Gaussian splatting from sparse multi-view images, requiring no ground-truth poses during training and inference. It employs a shared feature extraction backbone, enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Ranran Huang , Krystian Mikolajczyk

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

Reliable incremental estimation of camera poses and 3D reconstruction is key to enable various applications including robotics, interactive visualization, and augmented reality. However, this task is particularly challenging in dynamic…

Robotics · Computer Science 2025-12-09 Xingguang Zhong , Liren Jin , Marija Popović , Jens Behley , Cyrill Stachniss

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

Generating high-quality 3D content requires models capable of learning robust distributions of complex scenes and the real-world objects within them. Recent Gaussian-based 3D reconstruction techniques have achieved impressive results in…

Image and Video Processing · Electrical Eng. & Systems 2024-12-16 Kevin Miao , Harsh Agrawal , Qihang Zhang , Federico Semeraro , Marco Cavallo , Jiatao Gu , Alexander Toshev

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS often requires a large number of primitives to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Haoran Wang , Guoxi Huang , Fan Zhang , David Bull , Nantheera Anantrasirichai

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

This paper presents RoGSplat, a novel approach for synthesizing high-fidelity novel views of unseen human from sparse multi-view images, while requiring no cumbersome per-subject optimization. Unlike previous methods that typically struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Junjin Xiao , Qing Zhang , Yonewei Nie , Lei Zhu , Wei-Shi Zheng

3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Bo Jia , Yanan Guo , Ying Chang , Benkui Zhang , Ying Xie , Kangning Du , Lin Cao

In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We argue that the common practice of regressing Gaussian means as depths along camera rays…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Jiawei Ren , Michal Jan Tyszkiewicz , Jiahui Huang , Zan Gojcic

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang

Feature extraction, matching, structure from motion (SfM), and novel view synthesis (NVS) have traditionally been treated as separate problems with independent optimization objectives. We present GloSplat, a framework that performs…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Tianyu Xiong , Rui Li , Linjie Li , Jiaqi Yang

Planes are fundamental primitives of 3D sences, especially in man-made environments such as indoor spaces and urban streets. Representing these planes in a structured and parameterized format facilitates scene editing and physical…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Ruitong Gan , Junran Peng , Yang Liu , Chuanchen Luo , Qing Li , Zhaoxiang Zhang

We present billboard Splatting (BBSplat) - a novel approach for novel view synthesis based on textured geometric primitives. BBSplat represents the scene as a set of optimizable textured planar primitives with learnable RGB textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 David Svitov , Pietro Morerio , Lourdes Agapito , Alessio Del Bue