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pro vyhledávání: '"Bonde, Ujwal"'
Autor:
Warburg, Frederik, Hernandez-Juarez, Daniel, Tarrio, Juan, Vakhitov, Alexander, Bonde, Ujwal, Alcantarilla, Pablo F.
Active stereo systems are used in many robotic applications that require 3D information. These depth sensors, however, suffer from stereo artefacts and do not provide dense depth estimates.In this work, we present the first self-supervised depth comp
Externí odkaz:
http://arxiv.org/abs/2110.03234
In this work we introduce a new Bounding-Box Free Network (BBFNet) for panoptic segmentation. Panoptic segmentation is an ideal problem for proposal-free methods as it already requires per-pixel semantic class labels. We use this observation to explo
Externí odkaz:
http://arxiv.org/abs/2002.07705
A major element of depth perception and 3D understanding is the ability to predict the 3D layout of a scene and its contained objects for a novel pose. Indoor environments are particularly suitable for novel view prediction, since the set of objects
Externí odkaz:
http://arxiv.org/abs/1808.03609
Modern deep learning architectures produce highly accurate results on many challenging semantic segmentation datasets. State-of-the-art methods are, however, not directly transferable to real-time applications or embedded devices, since naive adaptat
Externí odkaz:
http://arxiv.org/abs/1805.04554
We present a novel deep architecture termed templateNet for depth based object instance recognition. Using an intermediate template layer we exploit prior knowledge of an object's shape to sparsify the feature maps. This has three advantages: (i) the
Externí odkaz:
http://arxiv.org/abs/1511.03244
Akademický článek
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Publikováno v:
IndraStra Global.
We consider the problem of extracting a signature representation of similar entities employing covariance descriptors. Covariance descriptors can efficiently represent objects and are robust to scale and pose changes. We posit that covariance descrip
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=issn23813652::989d2509209bcb2a167be11a27825732
https://igi.indrastra.com/items/show/197005
https://igi.indrastra.com/items/show/197005
Publikováno v:
Computer Vision - ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II; 2014, p520-535, 16p
Publikováno v:
Scale Space & Variational Methods in Computer Vision (9783642382666); 2013, p306-318, 13p
Publikováno v:
Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012); 1/ 1/2012, p2541-2544, 4p