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Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation

CVPR 2018 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised semantic segmentation · 884 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add AffinityNet random walk to CAMs (ablation)CAM label synthesis · PASCAL VOC 2012 train synthesized labelsmIoU: 48.0 -> 58.1Helped
Add dCRF refinement after random walk (ablation)CAM+RW label synthesis · PASCAL VOC 2012 train synthesized labelsmIoU: 58.1 -> 59.7Helped
Add AffinityNet random walk to CAMs (ablation)CAM label synthesis · PASCAL VOC 2012 val synthesized labelsmIoU: 46.8 -> 57.0Helped
Add dCRF refinement after random walk (ablation)CAM+RW label synthesis · PASCAL VOC 2012 val synthesized labelsmIoU: 57.0 -> 58.7Helped
Train a segmentation network using synthesized labels instead of using the label map directly (ablation)Ours-ResNet38 · PASCAL VOC 2012 valmIoU: 58.7 -> 61.7Helped
Use ResNet38 rather than DeepLab as the segmentation model backboneProposed segmentation pipeline · PASCAL VOC 2012 valmIoU: 58.4 -> 61.7Helped
Use ResNet38 rather than DeepLab as the segmentation model backboneProposed segmentation pipeline · PASCAL VOC 2012 testmIoU: 60.5 -> 63.7Helped
Apply multi-scale and horizontal-flip test-time augmentationOurs-ResNet38 · PASCAL VOC 2012 valmIoU: less than 2% in mIoUHelped

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