Scene Classification

Scene Classification is a task in which scenes from photographs are categorically classified. Unlike object classification, which focuses on classifying prominent objects in the foreground, Scene Classification uses the layout of objects within the scene, in addition to the ambient context, for classification.

Source: Scene classification with Convolutional Neural Networks

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 361–370 of 453 papers

Title	Date	Tasks	Status
Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network	May 18, 2018	Acoustic Scene ClassificationClassification	—Unverified
Automated Vision-based Bridge Component Extraction Using Multiscale Convolutional Neural Networks	May 15, 2018	ClassificationGeneral Classification	—Unverified
Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding	May 15, 2018	Scene ClassificationScene Understanding	—Unverified
Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey	Mar 9, 2018	3D Reconstructionobject-detection	—Unverified
HexaConv	Mar 6, 2018	Aerial Scene ClassificationScene Classification	CodeCode Available
Scenarios: A New Representation for Complex Scene Understanding	Feb 16, 2018	Image RetrievalObject Recognition	—Unverified
Exploring the significance of using perceptually relevant image decolorization method for scene classification	Dec 29, 2017	ClassificationGeneral Classification	—Unverified
Large-Scale 3D Scene Classification With Multi-View Volumetric CNN	Dec 26, 2017	ClassificationGeneral Classification	—Unverified
Exploring Models and Data for Remote Sensing Image Caption Generation	Dec 21, 2017	Caption GenerationImage-to-Text Retrieval	CodeCode Available
Deep Within-Class Covariance Analysis for Robust Audio Representation Learning	Nov 10, 2017	Acoustic Scene ClassificationClassification	—Unverified

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All datasets UC Merced Land Use Dataset Places365-Standard

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	µ2Net+ (ViT-L/16)	Accuracy (%)	100	—	Unverified
2	AGOS	Accuracy (%)	99.88	—	Unverified
3	LSE-Net	Accuracy (%)	99.78	—	Unverified
4	ResNet50	Accuracy (%)	99.61	—	Unverified
5	MSMatch	Accuracy (%)	98.33	—	Unverified
6	MIDC-Net	Accuracy (%)	97.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	iSQRT-COV-Net (ResNet-50)	Top 1 Error	43.68	—	Unverified
2	WaveMix	Top 1 Error	43.55	—	Unverified