SOTAVerified

Scene Parsing

Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description

Papers

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Showing 101–110 of 199 papers

TitleStatusHype
Non-parametric spatially constrained local prior for scene parsing on real-world data—0
Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions—0
Variational Context-Deformable ConvNets for Indoor Scene Parsing—0
Night-time Scene Parsing with a Large Real Dataset—0
Real-Time Panoptic Segmentation from Dense Detections—0
Unlocking the Full Potential of Small Data with Diverse SupervisionCode0
Differentiating Features for Scene Segmentation Based on Dedicated Attention Mechanisms—0
Adaptive Context Network for Scene Parsing—0
Cooperative Semantic Segmentation and Image Restoration in Adverse Environmental Conditions—0
Segmenting Ships in Satellite Imagery With Squeeze and Excitation U-Net—0
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All datasetsPGDP5KCityscapes test

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PGDPNetTotal Accuracy84.7—Unverified
2Inter-GPSTotal Accuracy27.3—Unverified
#ModelMetricClaimedVerifiedStatus
1VCD No CoarsemIoU82.3—Unverified