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
Deep Hierarchical Parsing for Semantic Segmentation—0
Deep Deconvolutional Networks for Scene Parsing—0
Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation—0
Beyond Forward Shortcuts: Fully Convolutional Master-Slave Networks (MSNets) with Backward Skip Connections for Semantic Segmentation—0
Interaction via Bi-Directional Graph of Semantic Region Affinity for Scene Parsing—0
Deep and Wide Multiscale Recursive Networks for Robust Image Labeling—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—0
Geometric Scene Parsing with Hierarchical LSTM—0
Cutting Edge: Soft Correspondences in Multimodal Scene Parsing—0
Image Parsing with a Wide Range of Classes and Scene-Level Context—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