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检索条件"机构=Visual Intelligence and Systems Group in the Computer Vision Lab at ETH Zurich"
40 条 记 录,以下是1-10 订阅
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FrontierNet: Learning visual Cues to Explore
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IEEE Robotics and Automation Letters 2025年 第7期10卷 6576-6583页
作者: Sun, Boyang Chen, Hanzhi Leutenegger, Stefan Cadena, Cesar Pollefeys, Marc Blum, Hermann ETH Zurich Computer Vision and Geometry Group Zurich8092 Switzerland Technical University of Munich Mobile Robotics Lab München80333 Germany ETH Zurich Mobile Robotics Lab Zurich8092 Switzerland ETH Zurich Robotic Systems Lab Zurich8092 Switzerland AI Lab Microsoft Mixed Reality Zurich8038 Switzerland University of Bonn Lamarr Institute for ML and AI Robot Perception and Learning Lab Bonn53115 Germany
Exploration of unknown environments is crucial for autonomous robots;it allows them to actively reason and decide on what new data to acquire for different tasks, such as mapping, object discovery, and environmental a... 详细信息
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Real-Time Monocular visual Odometry for On-Road Vehicles with 1-Point RANSAC
Real-Time Monocular Visual Odometry for On-Road Vehicles wit...
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Dynamic Maps 2010
作者: Scaramuzza, Davide Fraundorfer, Friedrich Siegwart, Roland Autonomous Systems Lab ETH Zurich Switzerland Computer Vision and Geometry Group ETH Zurich Switzerland
This paper presents a system capable of recovering the trajectory of a vehicle from the video input of a single camera at a very high frame-rate. The overall frame-rate is limited only by the feature extraction proces... 详细信息
来源: 评论
Learning Deep Sensorimotor Policies for vision-based Autonomous Drone Racing
arXiv
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arXiv 2022年
作者: Fu, Jiawei Song, Yunlong Wu, Yan Yu, Fisher Scaramuzza, Davide Robotics and Perception Group Department of Informatics University of Zurich Department of Neuroinformatics University of Zurich ETH Zurich Switzerland Visual Intelligence and Systems Group in the Computer Vision Lab at ETH Zurich Switzerland
unstructured environments, enabling various real-world applications. However, the lack of effective vision-based algorithms has been a stumbling block to achieving this goal. Existing systems often require hand-engine... 详细信息
来源: 评论
Learning Deep Sensorimotor Policies for vision-Based Autonomous Drone Racing
Learning Deep Sensorimotor Policies for Vision-Based Autonom...
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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)
作者: Jiawei Fu Yunlong Song Yan Wu Fisher Yu Davide Scaramuzza Department of Informatics Robotics and Perception Group University of Zurich Switzerland Department of Neuroinformatics University of Zurich and ETH Zurich Switzerland Visual Intelligence and Systems Group in the Computer Vision Lab ETH Zurich
The development of effective vision-based algorithms has been a significant challenge in achieving autonomous drones, which promise to offer immense potential for many real-world applications. This paper investigates ...
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Object Finding in Cluttered Scenes Using Interactive Perception
Object Finding in Cluttered Scenes Using Interactive Percept...
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Tonci Novkovic Remi Pautrat Fadri Furrer Michel Breyer Roland Siegwart Juan Nieto Autonomous Systems Lab ETH Zurich Switzerland Computer Vision and Geometry Group ETH Zurich Switzerland
Object finding in clutter is a skill that requires perception of the environment and in many cases physical interaction. In robotics, interactive perception defines a set of algorithms that leverage actions to improve... 详细信息
来源: 评论
Object finding in cluttered scenes using interactive perception
arXiv
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arXiv 2019年
作者: Novkovic, Tonci Pautrat, Remi Furrer, Fadri Breyer, Michel Siegwart, Roland Nieto, Juan Autonomous Systems Lab ETH Zurich8092 Switzerland Computer Vision and Geometry Group ETH Zurich8092 Switzerland
Object finding in clutter is a skill that requires both perception of the environment and in many cases physical interaction. In robotics, interactive perception defines a set of algorithms that leverage actions to im... 详细信息
来源: 评论
Incremental object database: Building 3D models from multiple partial observations
arXiv
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arXiv 2018年
作者: Furrer, Fadri Novkovic, Tonci Fehr, Marius Gawel, Abel Grinvald, Margarita Sattler, Torsten Siegwart, Roland Nieto, Juan Autonomous Systems Lab ETH Zurich8092 Switzerland Computer Vision Group Deparment of Computer Science ETH Zurich8092 Switzerland
Collecting 3D object datasets involves a large amount of manual work and is time consuming. Getting complete models of objects either requires a 3D scanner that covers all the surfaces of an object or one needs to rot... 详细信息
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Reinforced imitation: Sample efficient deep reinforcement learning for map-less navigation by leveraging prior demonstrations
arXiv
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arXiv 2018年
作者: Pfeiffer, M. Shukla, S. Turchetta, M. Cadena, C. Krause, A. Siegwart, R. Nieto, J. Autonomous Systems Lab Zurich Switzerland Computer Vision Lab Zurich Switzerland Learning & Adaptive Systems Group Zurich Switzerland Max Planck ETH Center for Learning Systems ETH Zurich Zurich Switzerland
This work presents a case study of a learning-based approach for target driven map-less navigation. The underlying navigation model is an end-to-end neural network which is trained using a combination of expert demons... 详细信息
来源: 评论
Omnidirectional visual obstacle detection using embedded FPGA
Omnidirectional visual obstacle detection using embedded FPG...
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IEEE/RSJ International Conference on Intelligent Robots and systems
作者: P. Gohl D. Honegger S. Omari M. Achtelik M. Pollefeys R. Siegwart ETH Zurich Autonomous Systems Lab Switzerland Computer Vision and Geometry Group ETH Zurich Switzerland Eidgenossische Technische Hochschule Zurich Zurich ZH CH
For autonomous navigation of Micro Aerial Vehicles (MAVs) in cluttered environments, it is essential to detect potential obstacles not only in the direction of flight but in their entire local environment. While there... 详细信息
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Renovating Names in Open-Vocabulary Segmentation Benchmarks  38
Renovating Names in Open-Vocabulary Segmentation Benchmarks
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38th Conference on Neural Information Processing systems, NeurIPS 2024
作者: Huang, Haiwen Peng, Songyou Zhang, Dan Geiger, Andreas Bosch IoC Lab University of Tübingen Germany Tübingen AI Center Germany Autonomous Vision Group University of Tübingen Germany ETH Zurich Switzerland MPI for Intelligent Systems Tübingen Germany Bosch Center for Artificial Intelligence Germany
Names are essential to both human cognition and vision-language models. Open-vocabulary models utilize class names as text prompts to generalize to categories unseen during training. However, the precision of these na...
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