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 81–90 of 199 papers

TitleStatusHype
Interaction via Bi-Directional Graph of Semantic Region Affinity for Scene Parsing—0
Class Attention Network for Semantic Segmentation of Remote Sensing Images—0
Minimal Solvers for Single-View Lens-Distorted Camera Auto-CalibrationCode1
Multi-layer Feature Aggregation for Deep Scene Parsing Models—0
A Dilated Residual Hierarchically Fashioned Segmentation Framework for Extracting Gleason Tissues and Grading Prostate Cancer from Whole Slide ImagesCode0
LID 2020: The Learning from Imperfect Data Challenge Results—0
Automatic Quantification of Settlement Damage using Deep Learning of Satellite Images—0
GINet: Graph Interaction Network for Scene Parsing—0
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene ParsingCode1
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph GenerationCode1
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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