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 101–110 of 453 papers

TitleStatusHype
Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices—0
Change-point Detection Methods for Body-Worn Video—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
Characterizing dynamically varying acoustic scenes from egocentric audio recordings in workplace setting—0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition—0
Acoustic Scene Classification Based on a Large-margin Factorized CNN—0
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification—0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction—0
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification—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