2022
DOI: 10.48550/arxiv.2201.08683
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A Comprehensive Study of Vision Transformers on Dense Prediction Tasks

Abstract: Convolutional Neural Networks (CNNs), architectures consisting of convolutional layers, have been the standard choice in vision tasks. Recent studies have shown that Vision Transformers (VTs), architectures based on self-attention modules, achieve comparable performance in challenging tasks such as object detection and semantic segmentation. However, the image processing mechanism of VTs is different from that of conventional CNNs. This poses several questions about their generalizability, robustness, reliabil… Show more

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