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 51–60 of 453 papers

TitleStatusHype
Audio Event-Relational Graph Representation Learning for Acoustic Scene ClassificationCode1
AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene ClassificationCode1
APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIPCode1
ApproxDet: Content and Contention-Aware Approximate Object Detection for MobilesCode1
Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing DomainCode1
Efficient Multi-Task RGB-D Scene Analysis for Indoor EnvironmentsCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene ClassificationCode1
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain ShiftCode1
Multi-Temporal Scene Classification and Scene Change Detection with Correlation based FusionCode1
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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