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Research map / Detection and segmentation / CNN features

Progressive Neighborhood Aggregation for Semantic Segmentation Refinement

AAAI 2023 · Detection and segmentation › CNN features · approach: Context modeling for semantic segmentation · 8 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add PNA to PSPPSP on Pascal VOC 2012 val · Pascal VOC 2012 valmIoU (%): 78.8% vs. 79.9%Helped
Add PNA to DeeplabV3DeeplabV3 with ResNet101 on CityScapes · CityScapes valmIoU (%): 80.5% vs. 81.3%Helped
Add PNA to FPNFPN on DeepGlobe · DeepGlobemIoU (%): 73.3% vs. 74.0%Helped
Add PNA to FPNFPN on Trans10k validation · Trans10k valmIoU (%): 89.5% and 90.7%Helped
Add PNA to FPNFPN on Trans10k test · Trans10k testmIoU (%): 90.3% and 91.0%Helped
Add PNA to DeeplabV3DeeplabV3 with ResNet50 on COCO-Stuff 10k · COCO-Stuff 10kmIoU (%): 34.7% and 37.0%Helped
Add SAM after NAM (ablation)FCN-OS-32 with ResNet50 on Pascal VOC 2012 · Pascal VOC 2012 valmIoU (%): 76.9 -> 78.6Helped
Add NAM to FCN-OS-32 (ablation)FCN-OS-32 with ResNet50 on Pascal VOC 2012 · Pascal VOC 2012 valmIoU (%): 67.1% vs. 76.9%Helped
Increase NAM window size from 5 to 7 (ablation)PNA on Pascal VOC 2012 · Pascal VOC 2012 valmIoU (%): 75.3 -> 75.8Helped
Increase NAM window size from 7 to 9 (ablation)PNA on Pascal VOC 2012 · Pascal VOC 2012 valmIoU (%): 75.8 -> 76.9Helped
Increase NAM window size from 9 to 11 (ablation)PNA on Pascal VOC 2012 · Pascal VOC 2012 valmIoU (%): 76.9 -> 76.9No clear effect

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