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 326–350 of 453 papers

TitleStatusHype
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision—0
Learning Visual Representation from Human Interactions—0
Less yet robust: crucial region selection for scene recognition—0
Leveraging feature communication in federated learning for remote sensing image classification—0
Leveraging Local Temporal Information for Multimodal Scene Classification—0
Leveraging Self-Supervised Learning for Scene Classification in Child Sexual Abuse Imagery—0
Locality-preserving Directions for Interpreting the Latent Space of Satellite Image GANs—0
Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines—0
Low-complexity acoustic scene classification in DCASE 2022 Challenge—0
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet—0
Low-complexity CNNs for Acoustic Scene Classification—0
Low-complexity CNNs for Acoustic Scene Classification—0
Low-complexity deep learning frameworks for acoustic scene classification—0
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms—0
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery—0
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification—0
Mid-level Visual Element Discovery as Discriminative Mode Seeking—0
Mini-batch graphs for robust image classification—0
Minimizing Risk Through Minimizing Model-Data Interaction: A Protocol For Relying on Proxy Tasks When Designing Child Sexual Abuse Imagery Detection Models—0
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning—0
Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network—0
Modality and Component Aware Feature Fusion For RGB-D Scene Classification—0
Multi-Feature Fusion-based Scene Classification Framework for HSR Images—0
Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification—0
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution—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