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Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussian Splatting (3DGS), where scenes are represented by a series…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Lanqing Guo , Yufei Wang , Hezhen Hu , Yan Zheng , Yeying Jin , Siyu Huang , Zhangyang Wang

Recently, 3D Gaussian Splatting (3DGS) has excelled in novel view synthesis (NVS) with its real-time rendering capabilities and superior quality. However, it encounters challenges for high-resolution novel view synthesis (HRNVS) due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Shiyun Xie , Zhiru Wang , Yinghao Zhu , Xu Wang , Chengwei Pan , Xiwang Dong

Reconstructing 3D scenes with high fidelity and efficiency remains a central pursuit in computer vision and graphics. Recent advances in 3D Gaussian Splatting (3DGS) enable photorealistic rendering with Gaussian primitives, yet the modeling…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Guangchi Fang , Bing Wang

Mirror-containing environments pose unique challenges for 3D reconstruction and novel view synthesis (NVS), as reflective surfaces introduce view-dependent distortions and inconsistencies. While cutting-edge methods such as Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Zijing Guo , Yunyang Zhao , Lin Wang

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu Zhang

We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that primarily perform novel-view synthesis from a sparse set of constrained images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Wongi Park , Jordan A. James , Myeongseok Nam , Minjae Lee , Soomok Lee , Sang-Hyun Lee , William J. Beksi

3D Gaussian Splatting (3DGS) has become a powerful representation for image-based object reconstruction, yet its performance drops sharply in sparse-view settings. Prior works address this limitation by employing diffusion models to repair…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Hung Nguyen , Runfa Li , An Le , Truong Nguyen

Sparse-view synthesis remains a challenging problem due to the difficulty of recovering accurate geometry and appearance from limited observations. While recent advances in 3D Gaussian Splatting (3DGS) have enabled real-time rendering with…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yi-Hsin Li , Thomas Sikora , Sebastian Knorr , Mårten Sjöström

We introduce a fully automatic pipeline for dynamic scene reconstruction from casually captured monocular RGB videos. Rather than designing a new scene representation, we enhance the priors that drive Dynamic Gaussian Splatting. Video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Meng-Li Shih , Ying-Huan Chen , Yu-Lun Liu , Brian Curless

Recently, reconstructing scenes from a single panoramic image using advanced 3D Gaussian Splatting (3DGS) techniques has attracted growing interest. Panoramic images offer a 360$\times$ 180 field of view (FoV), capturing the entire scene in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Zhijie Shen , Chunyu Lin , Shujuan Huang , Lang Nie , Kang Liao , Yao Zhao

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng

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

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces. This…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yanyan Li , Chenyu Lyu , Yan Di , Guangyao Zhai , Gim Hee Lee , Federico Tombari

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

We aim to tackle sparse-view reconstruction of a 360 3D scene using priors from latent diffusion models (LDM). The sparse-view setting is ill-posed and underconstrained, especially for scenes where the camera rotates 360 degrees around a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Soumava Paul , Christopher Wewer , Bernt Schiele , Jan Eric Lenssen

3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhibit substantial appearance variations from different…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jiayue Liu , Xiao Tang , Freeman Cheng , Roy Yang , Zhihao Li , Jianzhuang Liu , Yi Huang , Jiaqi Lin , Shiyong Liu , Xiaofei Wu , Songcen Xu , Chun Yuan