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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 453 papers

TitleStatusHype
In-domain representation learning for remote sensingCode0
A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene ClassificationCode0
City classification from multiple real-world sound scenesCode0
All grains, one scheme (AGOS): Learning multigrain instance representation for aerial scene classificationCode0
Centroid Based Concept Learning for RGB-D Indoor Scene ClassificationCode0
Visual and audio scene classification for detecting discrepancies in video: a baseline method and experimental protocolCode0
Unsupervised adversarial domain adaptation for acoustic scene classificationCode0
Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNsCode0
Kolmogorov-Arnold Network for Satellite Image Classification in Remote SensingCode0
Object Detectors Emerge in Deep Scene CNNsCode0
Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene ClassificationCode0
A Continual Development Methodology for Large-scale Multitask Dynamic ML SystemsCode0
Unsupervised Few-Shot Continual Learning for Remote Sensing Image Scene ClassificationCode0
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection InferenceCode0
Unsupervised Improvement of Audio-Text Cross-Modal RepresentationsCode0
An embarrassingly simple comparison of machine learning algorithms for indoor scene classificationCode0
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene ClassificationCode0
Bringing the Discussion of Minima Sharpness to the Audio Domain: a Filter-Normalised Evaluation for Acoustic Scene ClassificationCode0
What makes ImageNet good for transfer learning?Code0
Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement LearningCode0
Towards automatic initialization of registration algorithms using simulated endoscopy imagesCode0
Towards Better Exploiting Convolutional Neural Networks for Remote Sensing Scene ClassificationCode0
Pairwise Comparison Network for Remote Sensing Scene ClassificationCode0
Parsing Natural Scenes and Natural Language with Recursive Neural NetworksCode0
Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image EncodersCode0
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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