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检索条件"机构=The Computer Vision and Geometry Lab"
51 条 记 录,以下是1-10 订阅
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"Connected to the people": Social Inclusion & Cohesion in Action through a Cultural Heritage Digital Tool
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Proceedings of the ACM on Human-computer Interaction 2023年 第CSCW2期7卷 1-37页
作者: Nisi, Valentina Bala, Paulo Cesário, Vanessa James, Stuart Del Bue, Alessio Nunes, Nuno Jardim Instituto Superior Técnico U. Lisbon Lisbon Portugal Visual Geometry and Modelling Lab Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy
Current cultural policies are evolving from social inclusion (removing barriers and promoting equality for participation in culture) to social cohesion (fostering solid bonds between groups despite their differences).... 详细信息
来源: 评论
Active Visual Localization for Multi-Agent Collaboration: A Data-Driven Approach
Active Visual Localization for Multi-Agent Collaboration: A ...
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Matthew Hanlon Boyang Sun Marc Pollefeys Hermann Blum Computer Vision and Geometry Lab at ETH Zürich
Rather than having each newly deployed robot create its own map of its surroundings, the growing availability of SLAM-enabled devices provides the option of simply localizing in a map of another robot or device. In ca... 详细信息
来源: 评论
Active Visual Localization for Multi-Agent Collaboration: A Data-Driven Approach
arXiv
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arXiv 2023年
作者: Hanlon, Matthew Sun, Boyang Pollefeys, Marc Blum, Hermann Computer Vision and Geometry Lab ETH Zürich Switzerland
Rather than having each newly deployed robot create its own map of its surroundings, the growing availability of SLAM-enabled devices provides the option of simply localizing in a map of another robot or device. In ca... 详细信息
来源: 评论
A 3D Mixed Reality Interface for Human-Robot Teaming
A 3D Mixed Reality Interface for Human-Robot Teaming
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Jiaqi Chen Boyang Sun Marc Pollefeys Hermann Blum Computer Vision and Geometry Lab ETH Zürich Microsoft Mixed Reality & AI Lab Zürich
This paper presents a mixed-reality human-robot teaming system. It allows human operators to see in real-time where robots are located, even if they are not in line of sight. The operator can also visualize the map th... 详细信息
来源: 评论
Semantically Guided Feature Matching for Visual SLAM
Semantically Guided Feature Matching for Visual SLAM
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Oguzhan Ilter Iro Armeni Marc Pollefeys Daniel Barath Computer Vision and Geometry Group ETH Zurich Zurich Switzerland Microsoft Mixed Reality and AI Zurich Lab
We introduce a new algorithm that utilizes semantic information to enhance feature matching in visual SLAM pipelines. The proposed method constructs a high-dimensional semantic descriptor for each detected ORB feature... 详细信息
来源: 评论
A 3D Mixed Reality Interface for Human-Robot Teaming
arXiv
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arXiv 2023年
作者: Chen, Jiaqi Sun, Boyang Pollefeys, Marc Blum, Hermann Computer Vision and Geometry Lab ETH Zürich Switzerland Microsoft Mixed Reality AI Lab Zürich Switzerland
This paper presents a mixed-reality human-robot teaming system. It allows human operators to see in real-time where robots are located, even if they are not in line of sight. The operator can also visualize the map th... 详细信息
来源: 评论
Global Localization: Utilizing Relative Spatio-Temporal Geometric Constraints from Adjacent and Distant Cameras
arXiv
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arXiv 2023年
作者: Altillawi, Mohammad Pataki, Zador Li, Shile Liu, Ziyuan AI Robotics & Simulation Huawei Munich Research Center Germany Computer Vision Center Universitat Autònoma de Barcelona Spain Computer Vision and Geometry Lab ETH Zurich Switzerland
Re-localizing a camera from a single image in a previously mapped area is vital for many computer vision applications in robotics and augmented/virtual reality. In this work, we address the problem of estimating the 6... 详细信息
来源: 评论
Long-Term Invariant Local Features via Implicit Cross-Domain Correspondences
arXiv
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arXiv 2023年
作者: Pataki, Zador Altillawi, Mohammad Kanakis, Menelaos Pautrat, Rémi Shen, Fengyi Liu, Ziyuan Van Gool, Luc Pollefeys, Marc The Computer Vision and Geometry Lab Department of Computer Science ETH Zurich Switzerland The Computer Vision Center CVC-Barcelona The Intelligent Robotics Cloud Technology lab of Huawei-Munich Germany The Computer Vision Lab Department Electrical Engineering ETH Zurich Switzerland The Intelligent Robotics Cloud Technology lab of Huawei-Munich Germany The Intelligent Robotics Cloud Technology lab of Huawei-Munich Germany The Center for Processing Speech and Images KU Leuven The Computer Vision Lab ETH Zurich Switzerland
Modern learning-based visual feature extraction networks perform well in intra-domain localization, however, their performance significantly declines when image pairs are captured across long-term visual domain variat... 详细信息
来源: 评论
Learning-based Relational Object Matching Across Views
Learning-based Relational Object Matching Across Views
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Cathrin Elich Iro Armeni Martin R. Oswald Marc Pollefeys Joerg Stueckler Embodied Vision Group Max Planck Institute for Intelligent Systems Tuebingen Germany Max Planck ETH Center for Learning Systems Computer Vision and Geometry Lab ETH Zurich Switzerland University of Amsterdam Netherlands Microsoft Mixed Reality and AI Lab Zurich Switzerland
Intelligent robots require object-level scene understanding to reason about possible tasks and interactions with the environment. Moreover, many perception tasks such as scene reconstruction, image retrieval, or place...
来源: 评论
Learning-based Relational Object Matching Across Views
arXiv
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arXiv 2023年
作者: Elich, Cathrin Armeni, Iro Oswald, Martin R. Pollefeys, Marc Stueckler, Joerg Embodied Vision Group Max Planck Institute for Intelligent Systems Tuebingen Germany The Max Planck ETH Center for Learning Systems The Computer Vision and Geometry Lab ETH Zurich Switzerland University of Amsterdam Netherlands Microsoft Mixed Reality and AI Lab Zurich Switzerland
Intelligent robots require object-level scene understanding to reason about possible tasks and interactions with the environment. Moreover, many perception tasks such as scene reconstruction, image retrieval, or place... 详细信息
来源: 评论