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
RoadFormer+: Delivering RGB-X Scene Parsing through Scale-Aware Information Decoupling and Advanced Heterogeneous Feature Fusion—0
RoadFormer: Duplex Transformer for RGB-Normal Semantic Road Scene Parsing—0
SAI3D: Segment Any Instance in 3D Scenes—0
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering—0
Scale-Adaptive Convolutions for Scene Parsing—0
Scene Parsing by Integrating Function, Geometry and Appearance Models—0
Scene Parsing Through ADE20K Dataset—0
Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection—0
Scene Parsing with Integration of Parametric and Non-parametric Models—0
Scene Parsing with Object Instances and Occlusion Ordering—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