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Research map / Detection and segmentation / CNN features

Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF

CVPR 2017 · Detection and segmentation › CNN features · approach: Context modeling for semantic segmentation · 67 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add context CRF (ablation)Unary segmentation model · Pascal VOC 2012 valmIoU (%): 69.5 -> 76.3Helped
add structured patch prediction (ablation)Context CRF model · Pascal VOC 2012 valmIoU (%): 76.3 -> 76.8Helped
add guidance CRF (ablation)Structured patch prediction model · Pascal VOC 2012 valmIoU (%): 76.8 -> 77.7Helped
jointly train with MS-COCO (ablation)Guide model · Pascal VOC 2012 valmIoU (%): 77.7 -> 79.5Helped
use multi-scale testing (ablation)Joint model · Pascal VOC 2012 valmIoU (%): 79.5 -> 80.9Helped
use SegModel instead of DeepLab-v2Semantic segmentation system · Pascal VOC 2012 testmIoU (%): 79.7 -> 82.5Helped
use SegModel instead of LRR 4xSemantic segmentation system · Cityscapes testmIoU (%): 71.8 -> 79.2Helped

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