Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Will Maddern"'
Autor:
Akihiko Torii, Fredrik Kahl, Josef Sivic, Carl Toft, Daniel Safari, Lars Hammarstrand, Masatoshi Okutomi, Marc Pollefeys, Will Maddern, Tomas Pajdla, Torsten Sattler, Erik Stenborg
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2020, pp.14. ⟨10.1109/TPAMI.2020.3032010⟩
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, pp.14. ⟨10.1109/TPAMI.2020.3032010⟩
IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2020, pp.14. ⟨10.1109/TPAMI.2020.3032010⟩
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, pp.14. ⟨10.1109/TPAMI.2020.3032010⟩
International audience; Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to linkvirtual to real worlds. Practical visual localization approaches need to be robust to a wide variety o
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208899
ACCV (2)
ACCV (2)
The Guided Light Field Cost Volume (GLFCV) is a light field disparity estimation algorithm designed for (GPU) parallelization by refactoring the process, such that costly optimizations that combine and refine depth maps are simplified. The algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a0700ebc1c27f273a35ea486435335e
https://doi.org/10.1007/978-3-030-20890-5_17
https://doi.org/10.1007/978-3-030-20890-5_17
Publikováno v:
ICRA
This paper presents a weakly-supervised learning system for real-time road marking detection using images of complex urban environments obtained from a monocular camera. We avoid expensive manual labelling by exploiting additional sensor modalities t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fe4535210ce05a6213d3b51dec193a3
https://doi.org/10.1109/icra.2018.8460952
https://doi.org/10.1109/icra.2018.8460952
Autor:
Tomas Pajdla, Masatoshi Okutomi, Josef Sivic, Daniel Safari, Fredrik Kahl, Marc Pollefeys, Will Maddern, Torsten Sattler, Lars Hammarstrand, Erik Stenborg, Carl Toft, Akihiko Torii
Publikováno v:
CVPR
Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to link virtual to real worlds. Practical visual localization approaches need to be robust to a wide variety of viewing condition, in
Publikováno v:
ICRA
We present a self-supervised approach to ignoring "distractors" in camera images for the purposes of robustly estimating vehicle motion in cluttered urban environments. We leverage offline multi-session mapping approaches to automatically generate a
Publikováno v:
ICRA
We present a method of improving visual place recognition and metric localisation under very strong appear- ance change. We learn an invertable generator that can trans- form the conditions of images, e.g. from day to night, summer to winter etc. Thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fe636819e13f97a13afd66f72f9b403
http://arxiv.org/abs/1803.03341
http://arxiv.org/abs/1803.03341
Autor:
Paul Newman, Will Maddern
Publikováno v:
IROS
Real-time 3D perception is critical for localisation, mapping, path planning and obstacle avoidance for mobile robots and autonomous vehicles. For outdoor operation in real-world environments, 3D perception is often provided by sparse 3D LIDAR scanne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0d2212cc1aadd13aca240918aa3a840
https://doi.org/10.1109/iros.2016.7759342
https://doi.org/10.1109/iros.2016.7759342
We present a challenging new dataset for autonomous driving: the Oxford RobotCar Dataset. Over the period of May 2014 to December 2015 we traversed a route through central Oxford twice a week on average using the Oxford RobotCar platform, an autonomo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36d074b0783d7f1c13593eb6e20843bd
https://ora.ox.ac.uk/objects/uuid:c5266bad-e0f8-49f1-918e-1602ef935990
https://ora.ox.ac.uk/objects/uuid:c5266bad-e0f8-49f1-918e-1602ef935990
Publikováno v:
CVPR
We propose a direct monocular SLAM algorithm based on the Normalised Information Distance (NID) metric. In contrast to current state-of-the-art direct methods based on photometric error minimisation, our information-theoretic NID metric provides robu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a5ef657efb928a0431f0d133e8830b1
https://doi.org/10.1109/cvpr.2017.158
https://doi.org/10.1109/cvpr.2017.158
Publikováno v:
ICRA
We present a weakly-supervised approach to segmenting proposed drivable paths in images with the goal of autonomous driving in complex urban environments. Using recorded routes from a data collection vehicle, our proposed method generates vast quanti