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 51–60 of 199 papers

TitleStatusHype
Boosting Real-Time Driving Scene Parsing with Shared SemanticsCode0
Improving Panoptic Segmentation for Nighttime or Low-Illumination Urban Driving ScenesCode0
HAPNet: Toward Superior RGB-Thermal Scene Parsing via Hybrid, Asymmetric, and Progressive Heterogeneous Feature FusionCode0
A Data-efficient Framework for Robotics Large-scale LiDAR Scene ParsingCode0
Holistic 3D Scene Parsing and Reconstruction from a Single RGB ImageCode0
Unlocking the Full Potential of Small Data with Diverse SupervisionCode0
Auto-Retoucher(ART) - A framework for Background Replacement and Image EditingCode0
A Dilated Residual Hierarchically Fashioned Segmentation Framework for Extracting Gleason Tissues and Grading Prostate Cancer from Whole Slide ImagesCode0
Complete 3D Scene Parsing from an RGBD ImageCode0
Convolutional Neural Network Language ModelsCode0
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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