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 361–370 of 453 papers

TitleStatusHype
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification—0
Object based Scene Representations using Fisher Scores of Local Subspace Projections—0
Object-Level Context Modeling For Scene Classification with Context-CNN—0
One Class One Click: Quasi Scene-level Weakly Supervised Point Cloud Semantic Segmentation with Active Learning—0
On Frequency-Wise Normalizations for Better Recording Device Generalization in Audio Spectrogram Transformers—0
Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All Locations—0
Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification—0
On The Effect Of Coding Artifacts On Acoustic Scene Classification—0
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence—0
Acoustic Scene Classification with Squeeze-Excitation Residual Networks—0
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All datasetsUC Merced Land Use DatasetPlaces365-Standard

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