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 81–90 of 453 papers

Title	Date	Tasks	Status	Hype
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning	Nov 21, 2023	Acoustic Scene ClassificationAudio captioning	CodeCode Available	0
SpectralGPT: Spectral Remote Sensing Foundation Model	Nov 13, 2023	Change Detectionmodel	CodeCode Available	2
CD-COCO: A Versatile Complex Distorted COCO Database for Scene-Context-Aware Computer Vision	Nov 12, 2023	object-detectionObject Detection	CodeCode Available	1
Unlocking the capabilities of explainable fewshot learning in remote sensing	Oct 12, 2023	Scene Classification	—Unverified	0
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification	Oct 5, 2023	Acoustic Scene ClassificationGraph Representation Learning	CodeCode Available	1
Bringing the Discussion of Minima Sharpness to the Audio Domain: a Filter-Normalised Evaluation for Acoustic Scene Classification	Sep 28, 2023	Acoustic Scene ClassificationScene Classification	CodeCode Available	0
Locality-preserving Directions for Interpreting the Latent Space of Satellite Image GANs	Sep 26, 2023	Data AugmentationScene Classification	—Unverified	0
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification	Sep 17, 2023	Data AugmentationDiversity	—Unverified	0
Decoupling Common and Unique Representations for Multimodal Self-supervised Learning	Sep 11, 2023	Scene ClassificationSelf-Supervised Learning	CodeCode Available	1
SOAR: Scene-debiasing Open-set Action Recognition	Sep 3, 2023	Action RecognitionDecoder	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