EAPT: Efficient Attention Pyramid Transformer for Image Processing

Recent transformer-based models, especially patch-based methods, have shown huge potentiality in vision tasks. However, the split fixed-size patches divide the input features into the same size patches, which ignores the fact that vision elements are often various and thus may destroy the semantic i...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on multimedia Jg. 25; S. 50 - 61
Hauptverfasser:	Lin, Xiao, Sun, Shuzhou, Huang, Wei, Sheng, Bin, Li, Ping, Feng, David Dagan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Ablation attention mechanism classification Communication Convolutional neural networks Costs Encoding Feature extraction Formability Image classification Image processing Image segmentation Modules object detection Object recognition Patches (structures) pyramid Semantic segmentation Semantics Task analysis Transformer Transformers
ISSN:	1520-9210, 1941-0077
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!