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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–360 of 453 papers

TitleStatusHype
Attentive max feature map and joint training for acoustic scene classification—0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—0
Audio Scene Classification with Deep Recurrent Neural Networks—0
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions—0
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy—0
Automated Vision-based Bridge Component Extraction Using Multiscale Convolutional Neural Networks—0
Automatic Monitoring of Activities of Daily Living based on Real-life Acoustic Sensor Data: a preliminary study—0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features—0
A Volumetric Saliency Guided Image Summarization for RGB-D Indoor Scene Classification—0
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori—0
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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