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 31–40 of 453 papers

Title	Date	Tasks	Status	Hype
Backdoor Attacks for Remote Sensing Data with Wavelet Transform	Nov 15, 2022	Backdoor Attackbackdoor defense	CodeCode Available	1
Multi-dimensional Edge-based Audio Event Relational Graph Representation Learning for Acoustic Scene Classification	Oct 27, 2022	Acoustic Scene ClassificationGraph Representation Learning	CodeCode Available	1
WaveMix-Lite: A Resource-efficient Neural Network for Image Analysis	Oct 13, 2022	Efficient Neural NetworkGPU	CodeCode Available	1
Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding	Sep 12, 2022	Common Sense ReasoningScene Classification	CodeCode Available	1
Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments	Jul 10, 2022	Instance SegmentationPanoptic Segmentation	CodeCode Available	1
Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain	Jul 8, 2022	Land Cover Classificationobject-detection	CodeCode Available	1
BYOL-S: Learning Self-supervised Speech Representations by Bootstrapping	Jun 24, 2022	Scene ClassificationSelf-Supervised Learning	CodeCode Available	1
Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification	May 30, 2022	ClassificationRemote Sensing Image Classification	CodeCode Available	1
WaveMix: A Resource-efficient Neural Network for Image Analysis	May 28, 2022	Efficient Neural NetworkGPU	CodeCode Available	1
Debiased Self-Training for Semi-Supervised Learning	Feb 15, 2022	Object RecognitionScene Classification	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