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Related papers: DUSt3R: Geometric 3D Vision Made Easy

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Image datasets have been steadily growing in size, harming the feasibility and efficiency of large-scale 3D reconstruction methods. In this paper, a novel approach for scaling Multi-View Stereo (MVS) algorithms up to arbitrarily large…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Marco Orsingher , Paolo Zani , Paolo Medici , Massimo Bertozzi

Joint camera pose and dense geometry estimation from a set of images or a monocular video remains a challenging problem due to its computational complexity and inherent visual ambiguities. Most dense incremental reconstruction systems…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Kirill Mazur , Gwangbin Bae , Andrew J. Davison

While supervised stereo matching and monocular depth estimation have advanced significantly with learning-based algorithms, self-supervised methods using stereo images as supervision signals have received relatively less focus and require…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zihua Liu , Yizhou Li , Songyan Zhang , Masatoshi Okutomi

Highly accurate 3D volumetric reconstruction is still an open research topic where the main difficulty is usually related to merging some rough estimations with high frequency details. One of the most promising methods is the fusion between…

Computer Vision and Pattern Recognition · Computer Science 2019-08-05 Fotios Logothetis , Roberto Mecca , Roberto Cipolla

3D Gaussian Splatting (3DGS) enables efficient rendering, yet accurate surface reconstruction remains challenging due to unreliable geometric supervision. Existing approaches predominantly rely on depth-based reprojection to infer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Mai Su , Qihan Yu , Zhongtao Wang , Yilong Li , Chengwei Pan , Yisong Chen , Guoping Wang , Fei Zhu

Three-dimensional digital urban reconstruction from multi-view aerial images is a critical application where deep multi-view stereo (MVS) methods outperform traditional techniques. However, existing methods commonly overlook the key…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Yimei Liu , Yakun Ju , Yuan Rao , Hao Fan , Junyu Dong , Feng Gao , Qian Du

In recent years, 3D visual foundation models pioneered by pointmap-based approaches such as DUSt3R have attracted a lot of interest, achieving impressive accuracy and strong generalization across diverse scenes. However, these methods are…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shuang Guo , Filbert Febryanto , Lei Sun , Guillermo Gallego

Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

Real-time 3D reconstruction enables fast dense mapping of the environment which benefits numerous applications, such as navigation or live evaluation of an emergency. In contrast to most real-time capable approaches, our approach does not…

Computer Vision and Pattern Recognition · Computer Science 2021-04-22 Max Hermann , Boitumelo Ruf , Martin Weinmann

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

Intraoral 3D reconstruction is fundamental to digital orthodontics, yet conventional methods like intraoral scanning are inaccessible for remote tele-orthodontics, which typically relies on sparse smartphone imagery. While 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yiyi Miao , Taoyu Wu , Tong Chen , Ji Jiang , Zhe Tang , Zhengyong Jiang , Angelos Stefanidis , Limin Yu , Jionglong Su

Video stabilization aims to mitigate camera shake but faces a fundamental trade-off between geometric robustness and full-frame consistency. While 2D methods suffer from aggressive cropping, 3D techniques are often undermined by fragile…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Muhua Zhu , Xinhao Jin , Yu Zhang , Yifei Xue , Tie Ji , Yizhen Lao

DUSt3R has recently shown that one can reduce many tasks in multi-view geometry, including estimating camera intrinsics and extrinsics, reconstructing the scene in 3D, and establishing image correspondences, to the prediction of a pair of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Edgar Sucar , Zihang Lai , Eldar Insafutdinov , Andrea Vedaldi

Mirror reflections are common in everyday environments and can provide stereo information within a single capture, as the real and reflected virtual views are visible simultaneously. We exploit this property by treating the reflection as an…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Jing Wu , Zirui Wang , Iro Laina , Victor Adrian Prisacariu

Estimating precise metric depth and scene reconstruction from monocular endoscopy is a fundamental task for surgical navigation in robotic surgery. However, traditional stereo matching adopts binocular images to perceive the depth…

Robotics · Computer Science 2022-11-29 Ruofeng Wei , Bin Li , Hangjie Mo , Fangxun Zhong , Yonghao Long , Qi Dou , Yun-Hui Liu , Dong Sun

Image stitching aim to align two images taken from different viewpoints into one seamless, wider image. However, when the 3D scene contains depth variations and the camera baseline is significant, noticeable parallax occurs-meaning the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Muhua Zhu , Xinhao Jin , Chengbo Wang , Yongcong Zhang , Yifei Xue , Tie Ji , Yizhen Lao

This paper introduces a versatile paradigm for integrating multi-view reflectance (optional) and normal maps acquired through photometric stereo. Our approach employs a pixel-wise joint re-parameterization of reflectance and normal,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Baptiste Brument , Robin Bruneau , Yvain Quéau , Jean Mélou , François Bernard Lauze , Jean-Denis , Jean-Denis Durou , Lilian Calvet

Robust 3D geometry estimation from videos is critical for applications such as autonomous navigation, SLAM, and 3D scene reconstruction. Recent methods like DUSt3R demonstrate that regressing dense pointmaps from image pairs enables…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Xiaoshan Wu , Yifei Yu , Xiaoyang Lyu , Yihua Huang , Bo Wang , Baoheng Zhang , Zhongrui Wang , Xiaojuan Qi

Efficient and accurate 3D reconstruction is crucial for various applications, including augmented and virtual reality, medical imaging, and cinematic special effects. While traditional Multi-View Stereo (MVS) systems have been fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Umair Haroon , Ahmad AlMughrabi , Ricardo Marques , Petia Radeva

We present a real-time monocular dense SLAM system designed bottom-up from MASt3R, a two-view 3D reconstruction and matching prior. Equipped with this strong prior, our system is robust on in-the-wild video sequences despite making no…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Riku Murai , Eric Dexheimer , Andrew J. Davison