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 321–330 of 453 papers

TitleStatusHype
Environmental Sound Classification with Parallel Temporal-spectral Attention—0
Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs—0
Learning Important Spatial Pooling Regions for Scene Classification—0
Learning Instance Representation Banks for Aerial Scene Classification—0
Learning Receptive Fields for Pooling from Tensors of Feature Response—0
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision—0
Learning Visual Representation from Human Interactions—0
Less yet robust: crucial region selection for scene recognition—0
Leveraging feature communication in federated learning for remote sensing image classification—0
Leveraging Local Temporal Information for Multimodal Scene Classification—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