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

Computer Vision and Pattern Recognition · Computer Science 2018-08-29 Sebastian Bullinger , Christoph Bodensteiner , Michael Arens , Rainer Stiefelhagen

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Shuai Du , Youyi Zheng

We focus on the task of estimating a physically plausible articulated human motion from monocular video. Existing approaches that do not consider physics often produce temporally inconsistent output with motion artifacts, while…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Erik Gärtner , Mykhaylo Andriluka , Hongyi Xu , Cristian Sminchisescu

Drones have been widely utilized in various fields, but the number of drones being used illegally and for hazardous purposes has increased recently. To prevent those illegal drones, in this work, we propose a novel framework for…

Computer Vision and Pattern Recognition · Computer Science 2023-09-07 Seobin Hwang , Hanyoung Kim , Chaeyeon Heo , Youkyoung Na , Cheongeun Lee , Yeongjun Cho

The motion measurement of point targets constitutes a fundamental problem in photogrammetry, with extensive applications across various engineering domains. Reconstructing a point's 3D motion just from the images captured by only a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Huayu Huang , Banglei Guan , Yang Shang , Qifeng Yu

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

Realistic scene reconstruction in driving scenarios poses significant challenges due to fast-moving objects. Most existing methods rely on labor-intensive manual labeling of object poses to reconstruct dynamic objects in canonical space and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Ruida Zhang , Chengxi Li , Chenyangguang Zhang , Xingyu Liu , Haili Yuan , Yanyan Li , Xiangyang Ji , Gim Hee Lee

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

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

This paper addresses the challenge of novel-view synthesis and motion reconstruction of dynamic scenes from monocular video, which is critical for many robotic applications. Although Neural Radiance Fields (NeRF) and 3D Gaussian Splatting…

Robotics · Computer Science 2025-08-12 Xuesong Li , Lars Petersson , Vivien Rolland

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

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

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

In this paper, we describe a method to capture nearly entirely spherical (360 degree) depth information using two adjacent frames from a single spherical video with motion parallax. After illustrating a spherical depth information retrieval…

Computer Vision and Pattern Recognition · Computer Science 2022-06-15 Kenji Tanaka

Narrated instructional videos often show and describe manipulations of similar objects, e.g., repairing a particular model of a car or laptop. In this work we aim to reconstruct such objects and to localize associated narrations in 3D.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Dimitri Zhukov , Ignacio Rocco , Ivan Laptev , Josef Sivic , Johannes L. Schönberger , Bugra Tekin , Marc Pollefeys

We propose a new method to estimate the 6-dof trajectory of a flying object such as a quadrotor UAV within a 3D airspace monitored using multiple fixed ground cameras. It is based on a new structure from motion formulation for the 3D…

Computer Vision and Pattern Recognition · Computer Science 2017-11-22 Artem Rozantsev , Sudipta N. Sinha , Debadeepta Dey , Pascal Fua

3D object detection based on monocular camera data is a key enabler for autonomous driving. The task however, is ill-posed due to lack of depth information in 2D images. Recent deep learning methods show promising results to recover depth…

Computer Vision and Pattern Recognition · Computer Science 2020-05-18 Felix Nobis , Fabian Brunhuber , Simon Janssen , Johannes Betz , Markus Lienkamp

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods,…

Graphics · Computer Science 2020-09-22 Jiahui Lyu , Bojian Wu , Dani Lischinski , Daniel Cohen-Or , Hui Huang

We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image. While previous approaches address the deblurring problem only in the 2D image domain, our proposed…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Marc Pollefeys

This work presents new methods and algorithms for tracking the shape and trajectory of moving reflecting obstacles with broken rays, or rays reflecting at an obstacle. While in tomography the focus of the reconstruction method is to recover…

Graphics · Computer Science 2011-11-29 Kamen Lozev
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