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 391–400 of 453 papers

Title	Date	Tasks	Status
Spatial Information Considered Network for Scene Classification	May 18, 2020	ClassificationDiversity	CodeCode Available
Multi-level Cross-modal Feature Alignment via Contrastive Learning towards Zero-shot Classification of Remote Sensing Image Scenes	May 31, 2023	ClassificationContrastive Learning	CodeCode Available
Multimodal Remote Sensing Scene Classification Using VLMs and Dual-Cross Attention Networks	Dec 3, 2024	ClassificationScene Classification	CodeCode Available
Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection	Dec 1, 2018	Depth EstimationDepth Prediction	CodeCode Available
A multi-device dataset for urban acoustic scene classification	Jul 25, 2018	Acoustic Scene ClassificationClassification	CodeCode Available
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification	May 6, 2022	Aerial Scene ClassificationAll	CodeCode Available
SpectNet : End-to-End Audio Signal Classification Using Learnable Spectrograms	Nov 17, 2022	Acoustic Scene ClassificationAnomaly Detection	CodeCode Available
A Remote Sensing Image Dataset for Cloud Removal	Jan 3, 2019	Change DetectionCloud Removal	CodeCode Available
Ground-truth or DAER: Selective Re-query of Secondary Information	Sep 16, 2020	Object TrackingScene Classification	CodeCode Available
Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global Pooling	Jul 11, 2016	Acoustic Scene ClassificationAll	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