… module for semantic segmentation, we propose the novel Fully Transformer Networks,
where both encoder and decoder are based on pure Transformer with our specialized design. …

… In this paper we introduce Segmenter, a transformer model for semantic segmentation. …
network. We build on the recent Vision Transformer (ViT) and extend it to semantic segmentation. …

… Recent efforts in semantic segmentation using deep learning … the semantic segmentation
task based on transformer … a novel semantic segmentation network incorporating a transformer (…

… Transformer [9] and Twins [10], these methods mainly consider the design of the Transformer
… , a cutting-edge Transformer framework for semantic segmentation that jointly considers …

… paper: (1) We reformulate the image semantic segmentation problem from a sequence-to-…
the semantic segmentation task from a different perspective. Transformer Transformer and self-…

… critical for improving semantic segmentation accuracy, and long-range semantic information …
Therefore, we introduced the Transformer network as a subnetwork in the model for feature …

… part of an image transformer network has been the traditional approach for the semantic
segmentation task. However, such an approach leaves out the semantic context that an image …

… analysis of the applications in semantic segmentation, with a focus on … semantic segmentation
performance. We then delve into various application domains of semantic segmentation. …

… We evaluate HRViT for semantic segmentation on the Cityscapes and ADE20K datasets.
We employ a lightweight SegFormer [35] head based on the mmsegmentation framework [7]. …

… to exploit inner properties of transformer attention maps for multi-scale feature selection in
semantic segmentation. We analyze the properties of Vision Transformers and design TSG for …