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Anomaly segmentation is a critical task for driving applications, and it is approached traditionally as a per-pixel classification problem.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
Microsoft coco: Common objects in context
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Earlier work this paper cites.
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Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Simple and scalable predictive uncertainty estimation using deep ensembles
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Attention is all you need
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Earlier work this paper cites.
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Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
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Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving
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Deformable detr: Deformable transformers for end-to-end object detection
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The fishyscapes benchmark: Measuring blind spots in semantic segmentation
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Deep metric learning for open world semantic segmentation
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Segmentmeifyoucan: A benchmark for anomaly segmentation
Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Mathieu Salzmann, Pascal Fua, and Matthias Rottmann · 2021
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Entropy maximization and meta classification for out-of-distribution detection in semantic segmentation
Robin Chan, Matthias Rottmann, and Hanno Gottschalk · 2021
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Per-pixel classification is not all you need for semantic segmentation
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Pixel-wise anomaly detection in complex driving scenes
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Simple training strategies and model scaling for object detection
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Masked-attention mask transformer for universal image segmentation
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Pixel-by-pixel cross-domain alignment for few-shot semantic segmentation
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Pixel-wise energy-biased abstention learning for anomaly segmentation on complex urban driving scenes
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