Swin Transformer: Hierarchical Vision Transformer using Shifted Windows View a PDF of the paper titled Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, by Ze Liu and Yutong Lin and Yue Cao and Han Hu and Yixuan Wei and Zheng Zhang and Stephen Lin and Baining Guo
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows To address these differences, we propose a hierarchical Transformer whose representation is computed with Shifted windows The shifted windowing scheme brings greater efficiency by lim-iting self-attention computation to non-overlapping local windows while also allowing for cross-window connection
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows To address these differences, we propose a hierarchical Transformer whose representation is computed with Shifted windows The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection
Swin Transformer - GitHub It is basically a hierarchical Transformer whose representation is computed with shifted windows The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows To address these differences, we propose a hierarchical Transformer whose representation is computed with Shifted windows The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection
Ze Liu (刘泽) Ze Liu is currently a Member of Technical Staff at xAI He is recognized as a core contributor of Grok Vision, Grok Voice Mode, Grok3 and Grok2