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

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Showing 381–390 of 453 papers

Title	Date	Tasks	Status
Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification	Sep 1, 2018	General ClassificationImage Classification	CodeCode Available
A multiple-instance densely-connected ConvNet for aerial scene classification	Mar 3, 2020	Aerial Scene ClassificationClassification	CodeCode Available
Gradient-Guided Multiscale Focal Attention Network for Remote Sensing Scene Classification	Jul 16, 2024	Aerial Scene ClassificationRemote Sensing Image Classification	CodeCode Available
Efficient Similarity-based Passive Filter Pruning for Compressing CNNs	Oct 27, 2022	Acoustic Scene ClassificationScene Classification	CodeCode Available
DeepCorrect: Correcting DNN models against Image Distortions	May 5, 2017	ClassificationGeneral Classification	CodeCode Available
Decentralised Semi-supervised Onboard Learning for Scene Classification in Low-Earth Orbit	May 6, 2023	Federated LearningScene Classification	CodeCode Available
Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge	May 16, 2024	Acoustic Scene ClassificationScene Classification	CodeCode Available
HexaConv	Mar 6, 2018	Aerial Scene ClassificationScene Classification	CodeCode Available
Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events	Apr 10, 2019	Acoustic Scene ClassificationClassification	CodeCode Available
UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language Models	Dec 30, 2024	Question AnsweringScene Classification	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