PaperNeurIPS 2021 (arXiv 2021) · 2021
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
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SegFormer
Hierarchical Transformer encoder (MiT) producing multi-scale features at.
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2014Very Deep Convolutional Networks for Large-Scale Image RecognitionSimonyan, Zisserman2015Fully Convolutional Networks for Semantic SegmentationLong, Shelhamer, Darrell2016Deep Residual Learning for Image RecognitionHe, Zhang et al.2018DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFsChen, Papandreou et al.2020An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleDosovitskiy, Beyer et al.Built upon by · 0