Panoptic SegFormer

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A-ViT: Adaptive Tokens for Efficient Vision Transformer (2021, background): “…vision transformers have gained an increasing popularity in the vision community and they have been successfully applied to a broad range of vision applications, such as image classiﬁcation [11,16,32,43,48,55], object detection [3,7,39], image generation [20,21], and semantic segmentation [28,52].”
k-means Mask Transformer (2022, methodology): “When compared to more recent works (CMT-DeepLab [106], Panoptic Seg-Former [65], and Mask2Former [23]), k MaX-DeepLab still shows great performances without the advanced modules, such as deformable attention [116], cascaded transformer decoder [23], and uncertainty-based pointly supervision [56].”