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 41–50 of 199 papers

TitleStatusHype
Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detection—0
OneFormer: One Transformer to Rule Universal Image SegmentationCode3
GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing—0
VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum ModelingCode1
Boosting Night-time Scene Parsing with Learnable FrequencyCode1
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene ParsingCode1
Plane Geometry Diagram ParsingCode1
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene ParsingCode0
TO-Scene: A Large-scale Dataset for Understanding 3D Tabletop ScenesCode1
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation—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