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Found 5 papers, 2 papers with code
A Pytorch Reproduction of Masked Generative Image Transformer
We match the reported FID of 7. 32 with our replication and obtain 7. 59 with similar hyperparameters on ImageNet at resolution 512 x 512.
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation
To address this issue, we build upon the recent ObsNet approach by providing object instance knowledge to the observer.
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
In this paper, we tackle the detection of out-of-distribution (OOD) objects in semantic segmentation.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
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Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving
In this paper, we show how uncertainty estimation can be leveraged to enable safety critical image segmentation in autonomous driving, by triggering a fallback behavior if a target accuracy cannot be guaranteed.
This dataset does not exist: training models from generated images
This naturally brings the question: Can we train a classifier only on the generated data?
