LeMoRe combines Cartesian axis-wise views with nested attention to reach 33.5% mIoU on ADE20K at 0.8 GFLOPs and 1.6M parameters, a favorable efficiency point but not an accuracy leader.
Unetformer: A unet-like trans- former for efficient semantic segmentation of remote sensing urban scene imagery,
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LeMoRe: Learn More Details for Lightweight Semantic Segmentation
LeMoRe combines Cartesian axis-wise views with nested attention to reach 33.5% mIoU on ADE20K at 0.8 GFLOPs and 1.6M parameters, a favorable efficiency point but not an accuracy leader.