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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

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Showing 31–40 of 199 papers

Title	Date	Tasks	Status	Hype	Score
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	5
Fast and Accurate Scene Parsing via Bi-direction Alignment Networks	May 25, 2021	Scene ParsingSemantic Segmentation	CodeCode Available	1	5
3D-to-2D Distillation for Indoor Scene Parsing	Apr 6, 2021	Scene ParsingSemantic Parsing	CodeCode Available	1	5
DPF: Learning Dense Prediction Fields with Weak Supervision	Mar 29, 2023	Intrinsic Image DecompositionPrediction	CodeCode Available	1	5
Panoptic Segmentation	Jan 3, 2018	Image SegmentationInstance Segmentation	CodeCode Available	1	5
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene Parsing	Jul 18, 2020	Scene ParsingSemantic Segmentation	CodeCode Available	1	5
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck	Sep 17, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning	Jul 2, 2024	Contrastive LearningInstance Segmentation	CodeCode Available	1	5
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing	Mar 30, 2020	Scene ParsingSemantic Segmentation	CodeCode Available	1	5
Traffic Scene Parsing through the TSP6K Dataset	Mar 6, 2023	Autonomous DrivingDecoder	CodeCode Available	1	5

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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