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CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detection

NeurIPS 2020 · Detection and segmentation › CNN features · approach: RGB-D salient object detection · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add OIaSG saliency guidance (ablation)CoADNet-DR baseline · Cosal2015F-measure: 0.7402 -> 0.8023Helped
add OIaSG saliency guidance (ablation)CoADNet-DR baseline · CoSOD3kF-measure: 0.7099 -> 0.7489Helped
add GASA group-attentional aggregation (ablation)CoADNet-DR baseline · CoSOD3kF-measure: 0.7489 -> 0.8008Helped
add GASA group-attentional aggregation (ablation)CoADNet-DR baseline · Cosal2015F-measure: 0.8023 -> 0.8465Helped
add GGD gated group distribution (ablation)CoADNet-DR baseline · Cosal2015F-measure: 0.8465 -> 0.8682Helped
add GGD gated group distribution (ablation)CoADNet-DR baseline · CoSOD3kMAE: 0.0915 -> 0.0815Helped
replace deconvolution decoder with GCPD (ablation)CoADNet-DR baseline · Cosal2015F-measure: 0.8682 -> 0.8874Helped
replace deconvolution decoder with GCPD (ablation)CoADNet-DR baseline · CoSOD3kMAE: 0.0815 -> 0.0652Helped
use stronger backbone (Dilated ResNet-50 vs ResNet-50)CoADNet · MSRCF-measure: 0.8710 -> 0.8618Hurt
use stronger backbone (Dilated ResNet-50 vs ResNet-50)CoADNet · Cosal2015F-measure: 0.8771 -> 0.8874Helped
train on CoSOD3k (3316 images) instead of COCO-SEGCoADNet-V · Cosal2015F-measure: 0.8748 -> 0.8592Hurt

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