Transformer in image interpretation

Xiaojie Cui; Xuehua Chen; Jian Zhou; Dong Lin

doi:10.1117/12.2631151

18 March 2022 Transformer in image interpretation

Xiaojie Cui, Xuehua Chen, Jian Zhou, Dong Lin

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121680A (2022) https://doi.org/10.1117/12.2631151
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Different from convolutional neural network, transformer is able to model the long-distance relationship between the image pixels, thus it is now widely used in computer vision and remote sensing community. This paper comprehensively reviews the development of transformer models in automatic image interpretation tasks, especially the applications in image classification, object detection and semantic segmentation. Specifically, the popular transformer models are thoroughly analyzed and compared to acquire their advantages and limitations. Finally, current challenges and future works are concluded.

Citation Download Citation

Xiaojie Cui, Xuehua Chen, Jian Zhou, and Dong Lin "Transformer in image interpretation", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121680A (18 March 2022); https://doi.org/10.1117/12.2631151

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KEYWORDS

Transformers

Image segmentation

Remote sensing

Visual process modeling

Image classification

Computer programming

Machine vision

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