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 311–320 of 453 papers

TitleStatusHype
Knowledge-Aware Neuron Interpretation for Scene Classification—0
Kronecker Product Feature Fusion for Convolutional Neural Network in Remote Sensing Scene Classification—0
Label Tree Embeddings for Acoustic Scene Classification—0
Land Cover Classification via Multi-temporal Spatial Data by Recurrent Neural Networks—0
Language-Assisted 3D Scene Understanding—0
Large Margin Discriminant Dimensionality Reduction in Prediction Space—0
Large Margin Learning of Upstream Scene Understanding Models—0
Large-Scale 3D Scene Classification With Multi-View Volumetric CNN—0
Learning Class-to-Image Distance with Object Matchings—0
Learning Coarse-to-Fine Sparselets for Efficient Object Detection and Scene Classification—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