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 181–190 of 199 papers

TitleStatusHype
KE-GAN: Knowledge Embedded Generative Adversarial Networks for Semi-Supervised Scene Parsing—0
Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications—0
Learning Dynamic Hierarchical Models for Anytime Scene Labeling—0
Learning to Exploit Stability for 3D Scene Parsing—0
LID 2020: The Learning from Imperfect Data Challenge Results—0
LIDAR-based Driving Path Generation Using Fully Convolutional Neural Networks—0
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction—0
Location Augmentation for CNN—0
MCCD: Multi-Agent Collaboration-based Compositional Diffusion for Complex Text-to-Image Generation—0
Memory Based Video 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