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 321330 of 453 papers

TitleStatusHype
CNN depth analysis with different channel inputs for Acoustic Scene Classification0
Few-Shot Learning with Per-Sample Rich Supervision0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding0
Dynamic Traffic Scene Classification with Space-Time Coherence0
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes0
Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene ClassificationCode0
Acoustic Scene Classification by Implicitly Identifying Distinct Sound EventsCode0
Heterogeneous Multi-task Metric Learning across Multiple Domains0
Spatio-Temporal Attention Pooling for Audio Scene Classification0
Equivariant Multi-View NetworksCode0
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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