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
Deep Deconvolutional Networks for Scene Parsing—0
Hierarchical Scene Parsing by Weakly Supervised Learning with Image Descriptions—0
Deep and Wide Multiscale Recursive Networks for Robust Image Labeling—0
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense—0
Geometric Scene Parsing with Hierarchical LSTM—0
Improving Fully Convolution Network for Semantic Segmentation—0
Cutting Edge: Soft Correspondences in Multimodal Scene Parsing—0
Indoor Scene Parsing With Instance Segmentation, Semantic Labeling and Support Relationship Inference—0
Information Pursuit: A Bayesian Framework for Sequential Scene Parsing—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—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