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Fine-Grained Segmen...
Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization
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- Larsson, Måns, 1989 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Stenborg, Erik, 1980 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Toft, Carl, 1990 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Hammarstrand, Lars, 1979 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Sattler, Torsten, 1983 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kahl, Fredrik, 1972 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2019
- 2019
- Engelska.
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Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. ; :October, s. 31-41
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https://research.cha... (primary) (free)
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https://research.cha...
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https://doi.org/10.1...
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Abstract
Ämnesord
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- Long-term visual localization is the problem of estimating the camera pose of a given query image in a scene whose appearance changes over time. It is an important problem in practice, for example, encountered in autonomous driving. In order to gain robustness to such changes, long-term localization approaches often use segmantic segmentations as an invariant scene representation, as the semantic meaning of each scene part should not be affected by seasonal and other changes. However, these representations are typically not very discriminative due to the limited number of available classes. In this paper, we propose a new neural network, the Fine-Grained Segmentation Network (FGSN), that can be used to provide image segmentations with a larger number of labels and can be trained in a self-supervised fashion. In addition, we show how FGSNs can be trained to output consistent labels across seasonal changes. We demonstrate through extensive experiments that integrating the fine-grained segmentations produced by our FGSNs into existing localization algorithms leads to substantial improvements in localization performance.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Larsson, Måns, 1 ...
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Stenborg, Erik, ...
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Toft, Carl, 1990
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Hammarstrand, La ...
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Sattler, Torsten ...
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Kahl, Fredrik, 1 ...
- Om ämnet
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- NATURVETENSKAP
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NATURVETENSKAP
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och Data och informa ...
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och Datorseende och ...
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Proceedings of t ...
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Chalmers tekniska högskola