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ORCIDSvenja Uhlemeyer
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2020 – today
- 2023
[b1]Svenja Uhlemeyer:
Unsupervised Open World Recognition in Computer Vision. University of Wuppertal, Germany, 2023- [c4]Daniel Bogdoll, Svenja Uhlemeyer, Kamil Kowol, J. Marius Zöllner:
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey. IV 2023: 1-8 - [i6]Daniel Bogdoll, Svenja Uhlemeyer, Kamil Kowol, J. Marius Zöllner:
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey. CoRR abs/2302.02790 (2023) - [i5]Svenja Uhlemeyer, Julian Lienen, Eyke Hüllermeier, Hanno Gottschalk:
Detecting Novelties with Empty Classes. CoRR abs/2305.00983 (2023) - 2022
- [c3]Kira Maag
, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk:
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. ACCV (5) 2022: 476-494 - [c2]Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk:
Towards unsupervised open world semantic segmentation. UAI 2022: 1981-1991 - [i4]Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk:
Towards Unsupervised Open World Semantic Segmentation. CoRR abs/2201.01073 (2022) - [i3]Robin Chan, Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk:
Detecting and Learning the Unknown in Semantic Segmentation. CoRR abs/2202.08700 (2022) - [i2]Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk:
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. CoRR abs/2210.02074 (2022) - 2021
- [c1]Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Pascal Fua, Mathieu Salzmann, Matthias Rottmann:
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. NeurIPS Datasets and Benchmarks 2021 - [i1]Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Mathieu Salzmann, Pascal Fua, Matthias Rottmann:
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. CoRR abs/2104.14812 (2021)
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