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 121–130 of 199 papers

TitleStatusHype
Adaptive Pyramid Context Network for Semantic SegmentationCode0
Scene Parsing via Integrated Classification Model and Variance-Based RegularizationCode0
KE-GAN: Knowledge Embedded Generative Adversarial Networks for Semi-Supervised Scene Parsing—0
Structured Knowledge Distillation for Semantic SegmentationCode0
Multi-Scale Dual-Branch Fully Convolutional Network for Hand Parsing—0
Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More—0
CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing—0
GFF: Gated Fully Fusion for Semantic SegmentationCode1
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed dataCode0
What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing—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