Vision Transformer with Deformable Attention

Transformers have recently shown superior performances on various vision tasks. The large, sometimes even global, receptive field endows Transformer models with higher representation power over their CNN counterparts. Nevertheless, simply enlarging receptive field also gives rise to several concerns...

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Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 4784 - 4793
Hauptverfasser:	Xia, Zhuofan, Pan, Xuran, Song, Shiji, Li, Li Erran, Huang, Gao
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.06.2022
Schlagworte:	Adaptation models categorization Computational modeling Computer vision Data models Deformable models grouping and shape analysis Predictive models Recognition: detection retrieval; Deep learning architectures and techniques; Representation learning; Segmentation Transformers
ISSN:	1063-6919
Online-Zugang:	Volltext
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