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Drones have become essential tools for reconstructing wild scenes due to their outstanding maneuverability. Recent advances in radiance field methods have achieved remarkable rendering quality, providing a new avenue for 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Jiadong Tang , Yu Gao , Dianyi Yang , Liqi Yan , Yufeng Yue , Yi Yang

This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection…

Graphics · Computer Science 2025-10-01 Zhenyu Shu , Junlong Yu , Kai Chao , Shiqing Xin , Ligang Liu

Three-dimensional scene reconstruction from sparse-view satellite images is a long-standing and challenging task. While 3D Gaussian Splatting (3DGS) and its variants have recently attracted attention for its high efficiency, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Xuejun Huang , Xinyi Liu , Yi Wan , Zhi Zheng , Bin Zhang , Mingtao Xiong , Yingying Pei , Yongjun Zhang

Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have advanced 3D reconstruction and novel view synthesis, but remain heavily dependent on accurate camera poses and dense viewpoint coverage. These requirements limit their…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiahui Lu , Haihong Xiao , Xueyan Zhao , Wenxiong Kang

3D Gaussian Splatting achieves high-fidelity novel view synthesis, but its application to online long-sequence scenarios is still limited. Existing methods either rely on slow per-scene optimization or fail to provide efficient incremental…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Guichen Huang , Ruoyu Wang , Xiangjun Gao , Che Sun , Yuwei Wu , Shenghua Gao , Yunde Jia

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

Novel view synthesis (NVS) of static and dynamic urban scenes is essential for autonomous driving simulation, yet existing methods often struggle to balance reconstruction time with quality. While state-of-the-art neural radiance fields and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Sheng Miao , Sijin Li , Pan Wang , Dongfeng Bai , Bingbing Liu , Yue Wang , Andreas Geiger , Yiyi Liao

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, existing feed-forward methods still have potential for further…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianyu Chen , Wei Xiang , Kang Han , Yu Lu , Di Wu , Gaowen Liu , Ramana Rao Kompella

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

3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significantly deteriorates when test views deviate from the camera…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yutong Chen , Marko Mihajlovic , Xiyi Chen , Yiming Wang , Sergey Prokudin , Siyu Tang

Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based methods has advanced dynamic scene modeling, obtaining high-fidelity rendering and accurate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yinan Deng , Jianyu Dou , Jiahui Wang , Jingyu Zhao , Yi Yang , Yufeng Yue

Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Jiaxin Guo , Jiangliu Wang , Di Kang , Wenzhen Dong , Wenting Wang , Yun-hui Liu

3D Gaussian Splatting (3DGS) enables photorealistic rendering but suffers from artefacts due to sparse Structure-from-Motion (SfM) initialisation. To address this limitation, we propose GP-GS, a Gaussian Process (GP) based densification…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhihao Guo , Jingxuan Su , Chenghao Qian , Shenglin Wang , Jinlong Fan , Jing Zhang , Wei Zhou , Hadi Amirpour , Yunlong Zhao , Liangxiu Han , Peng Wang

3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometric priors. Existing methods have explored predicting point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Kanle Shi , Shenkun Xu , Yi Fang , Yu-Shen Liu

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

High-quality novel view synthesis for large-scale scenes presents a challenging dilemma in 3D computer vision. Existing methods typically partition large scenes into multiple regions, reconstruct a 3D representation using Gaussian splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Xiaohan Zhang , Sitong Wang , Yushen Yan , Yi Yang , Mingda Xu , Qi Liu

In this paper, we explore an open research problem concerning the reconstruction of 3D scenes from images. Recent methods have adopt 3D Gaussian Splatting (3DGS) to produce 3D scenes due to its efficient training process. However, these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Beizhen Zhao , Yifan Zhou , Zijian Wang , Hao Wang

We have recently seen great progress in 3D scene reconstruction through explicit point-based 3D Gaussian Splatting (3DGS), notable for its high quality and fast rendering speed. However, reconstructing dynamic scenes such as complex human…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Chao Zhang , Yifeng Zhou , Shuheng Wang , Wenfa Li , Degang Wang , Yi Xu , Shaohui Jiao

3D Gaussian Splatting (3DGS) has enabled the creation of highly realistic 3D scene representations from sets of multi-view images. However, inpainting missing regions, whether due to occlusion or scene editing, remains a challenging task,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Mahtab Dahaghin , Milind G. Padalkar , Matteo Toso , Alessio Del Bue
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