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Research map / Detection and segmentation / Open-set and few-shot detection

Sparse and Complete Latent Organization for Geospatial Semantic Segmentation

CVPR 2022 · Detection and segmentation › Open-set and few-shot detection · approach: Amodal and open-world instance segmentation · 20 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use SCO instead of PFSegNetResNet-50 segmentation on iSAID · iSAIDmIoU (%): 66.9% to 69.1%Helped
add attraction loss Lattr (ablation)FarSeg baseline · iSAIDmIoU (%): 63.7 -> 65.1Helped
add local repulsion loss Llocal_rep (ablation)FarSeg baseline · iSAIDmIoU (%): 63.7 -> 64.8Helped
combine attraction and local repulsion losses (ablation)FarSeg baseline · iSAIDmIoU (%): 63.7 -> 65.4Helped
add global repulsion loss Lglobal_rep (ablation)local prototypical contrastive loss · iSAIDmIoU (%): 65.4 -> 67.8Helped
add foreground-background repulsion loss Lfb_rep (ablation)local prototypical contrastive loss · iSAIDmIoU (%): 65.4 -> 67.4Helped
add global repulsion and foreground-background repulsion losses (ablation)local prototypical contrastive loss · iSAIDmIoU (%): 65.4 -> 69.1Helped
use patch shuffle instead of Cutout (ablation)SCO augmentation · iSAIDmIoU: 67.8 -> 69.1Helped
use patch shuffle instead of Mixup (ablation)SCO augmentation · iSAIDmIoU: 68.1 -> 69.1Helped
use patch shuffle instead of Manifold Mixup (ablation)SCO augmentation · iSAIDmIoU: 68.3 -> 69.1Helped
use patch shuffle instead of CutMix (ablation)SCO augmentation · iSAIDmIoU: 68.5 -> 69.1Helped
increase patch shuffle augmentation count beyond 15 (ablation)SCO · iSAIDmIoUHurt

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