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 241–250 of 453 papers

Title	Date	Tasks	Status	Hype
Deep Learning for Scene Classification: A Survey	Jan 26, 2021	ClassificationDeep Learning	—Unverified	0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks	Jan 25, 2021	Aerial Scene ClassificationScene Classification	—Unverified	0
Learning Visual Representation from Human Interactions	Jan 1, 2021	Action RecognitionDepth Estimation	—Unverified	0
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification	Dec 29, 2020	ClassificationEnsemble Learning	—Unverified	0
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping	Nov 5, 2020	Acoustic Scene ClassificationScene Classification	CodeCode Available	1
A Two-Stage Approach to Device-Robust Acoustic Scene Classification	Nov 3, 2020	Acoustic Scene ClassificationClassification	CodeCode Available	1
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles	Oct 21, 2020	Objectobject-detection	CodeCode Available	1
Exploiting Context for Robustness to Label Noise in Active Learning	Oct 18, 2020	Active LearningDocument Classification	—Unverified	0
What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions	Oct 16, 2020	Action RecognitionDepth Estimation	CodeCode Available	1
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples	Oct 2, 2020	ClassificationGeneral Classification	—Unverified	0

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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