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 71–80 of 199 papers

TitleStatusHype
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction—0
Re:PolyWorld - A Graph Neural Network for Polygonal Scene Parsing—0
Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving—0
Visual Traffic Knowledge Graph Generation from Scene Images—0
Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detection—0
GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing—0
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene ParsingCode0
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation—0
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling—0
ESCNet: Gaze Target Detection With the Understanding of 3D Scenes—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