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 291–300 of 453 papers

Title	Date	Tasks	Status	Hype
Multi-Scale Weight Sharing Network for Image Recognition	Jan 9, 2020	Object RecognitionScene Classification	—Unverified	0
Neural Architecture Search on Acoustic Scene Classification	Dec 30, 2019	Acoustic Scene ClassificationClassification	—Unverified	0
Environmental Sound Classification with Parallel Temporal-spectral Attention	Dec 14, 2019	Acoustic Scene ClassificationAudio Classification	—Unverified	0
Deliberative Explanations: visualizing network insecurities	Dec 1, 2019	AttributeObject Recognition	CodeCode Available	0
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification	Nov 28, 2019	ClassificationGeneral Classification	—Unverified	0
In-domain representation learning for remote sensing	Nov 15, 2019	Image ClassificationMulti-Label Image Classification	CodeCode Available	0
Characterizing dynamically varying acoustic scenes from egocentric audio recordings in workplace setting	Nov 10, 2019	Acoustic Scene ClassificationGeneral Classification	—Unverified	0
Centroid Based Concept Learning for RGB-D Indoor Scene Classification	Nov 1, 2019	ClassificationClustering	CodeCode Available	0
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification	Oct 30, 2019	Domain AdaptationFew-Shot Image Classification	CodeCode Available	0
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs	Oct 28, 2019	Acoustic Scene ClassificationScene Classification	CodeCode Available	1

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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