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 21–30 of 453 papers

Title	Date	Tasks	Status	Hype
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification	Oct 5, 2023	Acoustic Scene ClassificationGraph Representation Learning	CodeCode Available	1
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
Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion Models	Jul 31, 2023	Adversarial DefenseAdversarial Purification	CodeCode Available	1
Efficient Multi-Task Scene Analysis with RGB-D Transformers	Jun 8, 2023	Panoptic SegmentationScene Classification	CodeCode Available	1
Device-Robust Acoustic Scene Classification via Impulse Response Augmentation	May 12, 2023	Acoustic Scene ClassificationAudio Classification	CodeCode Available	1
Vision-Language Models in Remote Sensing: Current Progress and Future Trends	May 9, 2023	Image CaptioningImage Generation	CodeCode Available	1
CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding	Apr 19, 2023	Change DetectionContrastive Learning	CodeCode Available	1
APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP	Apr 12, 2023	Domain GeneralizationPrompt Learning	CodeCode Available	1
Universal Domain Adaptation for Remote Sensing Image Scene Classification	Jan 26, 2023	ClassificationDomain Adaptation	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