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

Showing 411420 of 453 papers

TitleStatusHype
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features0
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems0
Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type0
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization0
Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification0
Dynamic loss balancing and sequential enhancement for road-safety assessment and traffic scene classification0
Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis0
Dynamic texture and scene classification by transferring deep image features0
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Benchmark Results

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