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 121–130 of 453 papers

Title	Date	Tasks	Status	Score
Generalized Scene Classification from Small-Scale Datasets with Multi-Task Learning	Oct 8, 2021	ClassificationMulti-Task Learning	CodeCode Available	5
Efficient Multi-Resolution Fusion for Remote Sensing Data with Label Uncertainty	Feb 7, 2024	Scene Classification	CodeCode Available	5
All grains, one scheme (AGOS): Learning multigrain instance representation for aerial scene classification	Aug 25, 2022	Aerial Scene ClassificationAll	CodeCode Available	5
Domain Information Control at Inference Time for Acoustic Scene Classification	Jun 13, 2023	Acoustic Scene ClassificationDomain Generalization	CodeCode Available	5
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning	Nov 21, 2023	Acoustic Scene ClassificationAudio captioning	CodeCode Available	5
Acoustic scene analysis with multi-head attention networks	Sep 16, 2019	Acoustic Scene ClassificationGeneral Classification	CodeCode Available	5
Deliberative Explanations: visualizing network insecurities	Dec 1, 2019	AttributeObject Recognition	CodeCode Available	5
Efficient Similarity-based Passive Filter Pruning for Compressing CNNs	Oct 27, 2022	Acoustic Scene ClassificationScene Classification	CodeCode Available	5
DeepCorrect: Correcting DNN models against Image Distortions	May 5, 2017	ClassificationGeneral Classification	CodeCode Available	5
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems	Sep 15, 2022	Domain GeneralizationFine-Grained Image Classification	CodeCode Available	5

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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