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Related papers: Recovering 3D Planar Arrangements from Videos

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Accurate camera pose estimation from an image observation in a previously mapped environment is commonly done through structure-based methods: by finding correspondences between 2D keypoints on the image and 3D structure points in the map.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Fereidoon Zangeneh , Leonard Bruns , Amit Dekel , Alessandro Pieropan , Patric Jensfelt

We present a method to reconstruct the three-dimensional trajectory of a moving instance of a known object category in monocular video data. We track the two-dimensional shape of objects on pixel level exploiting instance-aware semantic…

Computer Vision and Pattern Recognition · Computer Science 2017-11-17 Sebastian Bullinger , Christoph Bodensteiner , Michael Arens , Rainer Stiefelhagen

We propose a method for 3D object reconstruction and 6D-pose estimation from 2D images that uses knowledge about object shape as the primary key. In the proposed pipeline, recognition and labeling of objects in 2D images deliver 2D segment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Marcell Wolnitza , Osman Kaya , Tomas Kulvicius , Florentin Wörgötter , Babette Dellen

Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment. Large-scale scenes and critical camera motions are great challenges facing the research community to…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Qi Cai , Lilian Zhang , Yuanxin Wu , Wenxian Yu , Dewen Hu

Recovering 4D from monocular video, which jointly estimates dynamic geometry and camera poses, is an inevitably challenging problem. While recent pointmap-based 3D reconstruction methods (e.g., DUSt3R) have made great progress in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Shizun Wang , Zhenxiang Jiang , Xingyi Yang , Xinchao Wang

Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-08 Kuldeep Purohit , Subeesh Vasu , M. Purnachandra Rao , A. N. Rajagopalan

Understanding the geometry and pose of objects in 2D images is a fundamental necessity for a wide range of real world applications. Driven by deep neural networks, recent methods have brought significant improvements to object pose…

Computer Vision and Pattern Recognition · Computer Science 2018-09-05 Jogendra Nath Kundu , Rahul M. V. , Aditya Ganeshan , R. Venkatesh Babu

Recovering dense and long-range pixel motion in videos is a challenging problem. Part of the difficulty arises from the 3D-to-2D projection process, leading to occlusions and discontinuities in the 2D motion domain. While 2D motion can be…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yuxi Xiao , Qianqian Wang , Shangzhan Zhang , Nan Xue , Sida Peng , Yujun Shen , Xiaowei Zhou

Three-dimensional (3D) reconstruction from two-dimensional images is an active research field in computer vision, with applications ranging from navigation and object tracking to segmentation and three-dimensional modeling. Traditionally,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Sierra Bonilla , Chiara Di Vece , Rema Daher , Xinwei Ju , Danail Stoyanov , Francisco Vasconcelos , Sophia Bano

Spatial relationships between objects provide important information for text-based image retrieval. As users are more likely to describe a scene from a real world perspective, using 3D spatial relationships rather than 2D relationships that…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Ang Li , Jin Sun , Joe Yue-Hei Ng , Ruichi Yu , Vlad I. Morariu , Larry S. Davis

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Petr Hruby , Tomas Pajdla

Conventional image motion based structure from motion methods first compute optical flow, then solve for the 3D motion parameters based on the epipolar constraint, and finally recover the 3D geometry of the scene. However, errors in optical…

Computer Vision and Pattern Recognition · Computer Science 2018-05-18 Francisco Barranco , Cornelia Fermüller , Yiannis Aloimonos , Eduardo Ros

Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world. It is extremely challenging to acquire their 3D digital models using traditional image-based or depth-based…

Graphics · Computer Science 2020-05-21 Peng Wang , Lingjie Liu , Nenglun Chen , Hung-Kuo Chu , Christian Theobalt , Wenping Wang

Photomechanics is a crucial branch of solid mechanics. The localization of point targets constitutes a fundamental problem in optical experimental mechanics, with extensive applications in various missions of UAVs. Localizing moving targets…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Huayu Huang , Banglei Guan , Yang Shang , Qifeng Yu

Man-made environments typically comprise planar structures that exhibit numerous geometric relationships, such as parallelism, coplanarity, and orthogonality. Making full use of these relationships can considerably improve the robustness of…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Yangbin Lin , Jialian Li , Cheng Wang , Zhonggui Chen , Zongyue Wang , Jonathan Li

We present a method to reconstruct the 3D trajectory of an airborne robotic system only from videos recorded with cameras that are unsynchronized, may feature rolling shutter distortion, and whose viewpoints are unknown. Our approach…

Robotics · Computer Science 2020-07-30 Jingtong Li , Jesse Murray , Dorina Ismaili , Konrad Schindler , Cenek Albl

Dense 3D scene reconstruction from an ordered sequence or unordered image collections is a critical step when bringing research in computer vision into practical scenarios. Following the paradigm introduced by DUSt3R, which unifies an image…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuqi Wu , Wenzhao Zheng , Jie Zhou , Jiwen Lu

Extracting planes from a 3D scene is useful for downstream tasks in robotics and augmented reality. In this paper we tackle the problem of estimating the planar surfaces in a scene from posed images. Our first finding is that a surprisingly…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jamie Watson , Filippo Aleotti , Mohamed Sayed , Zawar Qureshi , Oisin Mac Aodha , Gabriel Brostow , Michael Firman , Sara Vicente

Capturing and reconstructing a human actor's motion is important for filmmaking and gaming. Currently, motion capture systems with static cameras are used for pixel-level high-fidelity reconstructions. Such setups are costly, require…

Robotics · Computer Science 2023-08-02 Qingyuan Jiang , Volkan Isler

We explain theoretically how to reconstruct the 3D scene from successive frames in order to see the video in 3D. To do this, features, associated to moving rigid objects in 3D, are extracted in frames and matched. The vanishing point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-30 Slimane Larabi
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