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Coordinate Attention for Efficient Mobile Network Design

CVPR 2021 · Detection and segmentation › CNN features · approach: Efficient network training and design · 6,279 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add coordinate attention instead of SEMobileNetV2 · ImageNetTop-1 accuracy: 73.5_{+1.2} -> 74.3_{+2.0}Helped
Use both horizontal and vertical attention rather than only one direction (ablation)MobileNetV2 coordinate attention · ImageNetTop-1 accuracy: 73.5_{+1.2} -> 74.3_{+2.0}Helped
Replace coordinate attention with horizontal-only attention (ablation)MobileNetV2 coordinate attention · ImageNetTop-1 accuracy: 74.3_{+2.0} -> 73.5_{+1.2}Hurt
Replace coordinate attention with vertical-only attention (ablation)MobileNetV2 coordinate attention · ImageNetTop-1 accuracy: 74.3_{+2.0} -> 73.5_{+1.2}Hurt
Reduce the coordinate-attention reduction ratio from 32 to 16 (ablation)MobileNetV2 + CA · ImageNetTop-1 accuracy: 74.3_{+2.0} -> 74.7_{+2.4}Helped
Add coordinate attention instead of SEMobileNeXt · ImageNetTop-1 accuracy: 74.7_{+0.7} -> 75.2_{+1.2}Helped
Replace SE with coordinate attentionEfficientNet-b0 · ImageNetTop-1 accuracy: 76.3 -> 76.9Helped
Add coordinate attentionMobileNetV2 · COCO 2017 validation, SSDLite320AP: 22.3 -> 24.5Helped
Add SE or CBAMMobileNetV2 · Pascal VOC 2007 test, SSDLite320mAP: 71.7 -> 71.7No clear effect
Add coordinate attentionMobileNetV2 · Pascal VOC 2007 test, SSDLite320mAP: 71.7 -> 73.1Helped
Add coordinate attention instead of SEMobileNetV2 · Pascal VOC 2012 validation, output stride 16mIoU: 71.69 -> 73.32Helped
Add coordinate attention instead of SEMobileNetV2 · Cityscapes validation, output stride 8mIoU: 72.2 -> 74.0Helped

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