An Information-Theoretic Method to Automatic Shortcut Avoidance and Domain Generalization for Dense Prediction Tasks
Deep convolutional neural networks for dense prediction tasks are commonly optimized using synthetic data, as generating pixel-wise annotations for real-world data is laborious. However, the synthetically trained models do not generalize well to real-world environments. This poor "synthetic to...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 9 vom: 01. Sept., Seite 10615-10631
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| Auteur principal: |
Chuah, WeiQin
(Auteur) |
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| Autres auteurs: |
Tennakoon, Ruwan,
Hoseinnezhad, Reza,
Suter, David,
Bab-Hadiashar, Alireza |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2023
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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