SOTAVerified

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 226–250 of 453 papers

TitleStatusHype
Multi-Feature Fusion-based Scene Classification Framework for HSR Images—0
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report—0
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval—0
Mini-batch graphs for robust image classification—0
Attentive max feature map and joint training for acoustic scene classification—0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network—0
Remote Sensing Image Classification with the SEN12MS DatasetCode1
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification—0
SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification—0
Environmental sound analysis with mixup based multitask learning and cross-task fusion—0
A Hierarchical Approach to Remote Sensing Scene Classification—0
Multi-Modal RGB-D Scene Recognition Across DomainsCode0
MSMatch: Semi-Supervised Multispectral Scene Classification with Few LabelsCode1
Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech—0
Scene Retrieval for Contextual Visual Mapping—0
Deep Learning for Scene Classification: A Survey—0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks—0
Learning Visual Representation from Human Interactions—0
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification—0
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency DampingCode1
A Two-Stage Approach to Device-Robust Acoustic Scene ClassificationCode1
ApproxDet: Content and Contention-Aware Approximate Object Detection for MobilesCode1
Exploiting Context for Robustness to Label Noise in Active Learning—0
What Can You Learn from Your Muscles? Learning Visual Representation from Human InteractionsCode1
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples—0
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All datasetsUC Merced Land Use DatasetPlaces365-Standard

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100—Unverified
2AGOSAccuracy (%)99.88—Unverified
3LSE-NetAccuracy (%)99.78—Unverified
4ResNet50Accuracy (%)99.61—Unverified
5MSMatchAccuracy (%)98.33—Unverified
6MIDC-NetAccuracy (%)97.4—Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68—Unverified
2WaveMixTop 1 Error43.55—Unverified