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 161–170 of 453 papers

Title	Date	Tasks	Status
Deriving Visual Semantics from Spatial Context: An Adaptation of LSA and Word2Vec to generate Object and Scene Embeddings from Images	Sep 20, 2020	ObjectScene Classification	—Unverified
Deep Scene Image Classification With the MFAFVNet	Oct 1, 2017	ClassificationGeneral Classification	—Unverified
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition	May 28, 2014	Event DetectionObject	—Unverified
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy	Apr 25, 2022	Scene ClassificationTransfer Learning	—Unverified
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding	Jun 7, 2019	Depth EstimationGeneral Classification	—Unverified
Deep Neural Decision Forest for Acoustic Scene Classification	Mar 7, 2022	Acoustic Scene ClassificationClassification	—Unverified
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions	May 28, 2021	ClassificationData Augmentation	—Unverified
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification	Jun 15, 2021	Aerial Scene ClassificationClassification	—Unverified
Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type	Jul 25, 2023	Explainable artificial intelligenceScene Classification	—Unverified
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality	Mar 31, 2022	Acoustic Scene ClassificationDictionary Learning	—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