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Related papers: Semantic-Guided 3D Gaussian Splatting for Transien…

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Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results. However, this method faces challenges in modeling specular…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Zhiru Wang , Shiyun Xie , Chengwei Pan , Guoping Wang

Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-centric or rely on costly training for inter-object reasoning.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yaxu Xie , Abdalla Arafa , Alireza Javanmardi , Christen Millerdurai , Jia Cheng Hu , Shaoxiang Wang , Alain Pagani , Didier Stricker

Recently, several studies have combined Gaussian Splatting to obtain scene representations with language embeddings for open-vocabulary 3D scene understanding. While these methods perform well, they essentially require very dense multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Jun Hu , Zhang Chen , Zhong Li , Yi Xu , Juyong Zhang

While 3D Gaussian splatting (3DGS) offers explicit and efficient scene representations for cone-beam computed tomography reconstruction, conventional photometric optimization inherently suffers from spectral bias under ultra sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Jian Lin , Jiancheng Fang , Shaoyu Wang , Changan Lai , Yikun Zhang , Yang Chen , Qiegen Liu

In this paper, we aim ambitiously for a realistic yet challenging problem, namely, how to reconstruct high-quality 3D scenes from sparse low-resolution views that simultaneously suffer from deficient perspectives and clarity. Whereas…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Yecong Wan , Mingwen Shao , Yuanshuo Cheng , Wangmeng Zuo

Reconstructing 3D scenes from sparse images remains a challenging task due to the difficulty of recovering accurate geometry and texture without optimization. Recent approaches leverage generalizable models to generate 3D scenes using 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Bing He , Jingnan Gao , Yunuo Chen , Ning Cao , Gang Chen , Zhengxue Cheng , Li Song , Wenjun Zhang

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

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

As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dynamic scene. However, previous works fail to accurately…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Jeongmin Bae , Seoha Kim , Youngsik Yun , Hahyun Lee , Gun Bang , Youngjung Uh

Precisely perceiving the geometric and semantic properties of real-world 3D objects is crucial for the continued evolution of augmented reality and robotic applications. To this end, we present Foundation Model Embedded Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Xingxing Zuo , Pouya Samangouei , Yunwen Zhou , Yan Di , Mingyang Li

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

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 recent years, there has been a growing demand to stylize a given 3D scene to align with the artistic style of reference images for creative purposes. While 3D Gaussian Splatting(GS) has emerged as a promising and efficient method for…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yangkai Lin , Jiabao Lei , Kui jia

We present Gaussian See, Gaussian Do, a novel approach for semantic 3D motion transfer from multiview video. Our method enables rig-free, cross-category motion transfer between objects with semantically meaningful correspondence. Building…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Yarin Bekor , Gal Michael Harari , Or Perel , Or Litany

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

Recently, 3D Gaussian splatting (3DGS) has gained considerable attentions in the field of novel view synthesis due to its fast performance while yielding the excellent image quality. However, 3DGS in sparse-view settings (e.g., three-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hyunwoo Park , Gun Ryu , Wonjun Kim

Recent years have witnessed substantial advancements in the field of 3D reconstruction from 2D images, particularly following the introduction of the neural radiance field (NeRF) technique. However, reconstructing a 3D high dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jiahao Wu , Lu Xiao , Rui Peng , Kaiqiang Xiong , Ronggang Wang

We propose an adaptive sampling framework for 3D Gaussian Splatting (3DGS) that leverages comprehensive multi-view photometric error signals within a unified Metropolis-Hastings approach. Vanilla 3DGS heavily relies on heuristic-based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Hyunjin Kim , Haebeom Jung , Jaesik Park

We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without altering their main details, all in a matter of minutes on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Francesco Palandra , Andrea Sanchietti , Daniele Baieri , Emanuele Rodolà