32 citations · 95 across the 11 of their papers we have counts for
4 papers · 1 filter
Demystify Transformers & Convolutions in Modern Image Deep Networks
Xiaowei Hu, Min Shi, Weiyun Wang +9
Vision transformers have gained popularity recently, leading to the development of new vision backbones with improved features and consistent performance gains. However, these adva…
CATrans: Context and Affinity Transformer for Few-Shot Segmentation
Shan Zhang, Tianyi Wu, Sitong Wu +1
Few-shot segmentation (FSS) aims to segment novel categories given scarce annotated support images. The crux of FSS is how to aggregate dense correlations between support and query…
Feature Selective Transformer for Semantic Image Segmentation
Fangjian Lin, Tianyi Wu, Sitong Wu +2
Recently, it has attracted more and more attentions to fuse multi-scale features for semantic image segmentation. Various works were proposed to employ progressive local or global…
StructToken : Rethinking Semantic Segmentation with Structural Prior
Fangjian Lin, Zhanhao Liang, Sitong Wu +3
In previous deep-learning-based methods, semantic segmentation has been regarded as a static or dynamic per-pixel classification task, \textit{i.e.,} classify each pixel representa…