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
Fully Decoupled Residual ConvNet for Real-Time Railway Scene Parsing of UAV Aerial Images—0
MSP : Refine Boundary Segmentation via Multiscale Superpixel—0
TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing—0
Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsing—0
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models—0
Memory Based Video Scene Parsing—0
Window Detection In Facade Imagery: A Deep Learning Approach Using Mask R-CNN—0
VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild—0
Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos—0
Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired—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