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 341–350 of 453 papers

Title	Date	Tasks	Status
Training neural audio classifiers with few data	Oct 24, 2018	Acoustic Scene ClassificationGeneral Classification	CodeCode Available
Deep Within-Class Covariance Analysis for Robust Deep Audio Representation Learning	Oct 22, 2018	Acoustic Scene ClassificationClassification	—Unverified
SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitro	Sep 13, 2018	Data AugmentationGeneral Classification	CodeCode Available
CNNs for Surveillance Footage Scene Classification	Sep 8, 2018	ClassificationGeneral Classification	—Unverified
CNNs-based Acoustic Scene Classification using Multi-Spectrogram Fusion and Label Expansions	Sep 5, 2018	Acoustic Scene ClassificationClassification	—Unverified
Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification	Sep 1, 2018	General ClassificationImage Classification	CodeCode Available
Hierarchy of Alternating Specialists for Scene Recognition	Sep 1, 2018	Scene ClassificationScene Recognition	—Unverified
Unsupervised adversarial domain adaptation for acoustic scene classification	Aug 17, 2018	Acoustic Scene ClassificationClassification	CodeCode Available
Acoustic Scene Classification: A Competition Review	Aug 2, 2018	Acoustic Scene ClassificationClassification	—Unverified
A multi-device dataset for urban acoustic scene classification	Jul 25, 2018	Acoustic Scene ClassificationClassification	CodeCode Available

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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