Hierarchical Invariance for Robust and Interpretable Vision Tasks at Larger Scales

Developing robust and interpretable vision systems is a crucial step towards trustworthy artificial intelligence. In this regard, a promising paradigm considers embedding task-required invariant structures, e.g., geometric invariance, in the fundamental image representation. However, such invariant...

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Hauptverfasser:	Qi, Shuren, Zhang, Yushu, Wang, Chao, Xia, Zhihua, Cao, Xiaochun, Weng, Jian
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Learning
Online-Zugang:	Volltext bestellen
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