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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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 21–30 of 199 papers

Title	Date	Tasks	Status	Hype
Global Aggregation then Local Distribution for Scene Parsing	Jul 28, 2021	Scene ParsingSegmentation	CodeCode Available	1
Resource Efficient Mountainous Skyline Extraction using Shallow Learning	Jul 23, 2021	geo-localizationScene Parsing	CodeCode Available	1
Part-aware Panoptic Segmentation	Jun 11, 2021	Image SegmentationPanoptic Segmentation	CodeCode Available	1
Fast and Accurate Scene Parsing via Bi-direction Alignment Networks	May 25, 2021	Scene ParsingSemantic Segmentation	CodeCode Available	1
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning	May 10, 2021	Arithmetic ReasoningGeometry Problem Solving	CodeCode Available	1
Editable Free-viewpoint Video Using a Layered Neural Representation	Apr 30, 2021	DisentanglementNeRF	CodeCode Available	1
3D-to-2D Distillation for Indoor Scene Parsing	Apr 6, 2021	Scene ParsingSemantic Parsing	CodeCode Available	1
Evidential fully convolutional network for semantic segmentation	Mar 25, 2021	DecoderScene Parsing	CodeCode Available	1
AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing	Mar 10, 2021	Scene ParsingSegmentation	CodeCode Available	1
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes	Jan 15, 2021	All-day Semantic SegmentationAutonomous Vehicles	CodeCode Available	1

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All datasets PGDP5K Cityscapes test

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PGDPNet	Total Accuracy	84.7	—	Unverified
2	Inter-GPS	Total Accuracy	27.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VCD No Coarse	mIoU	82.3	—	Unverified