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 1–25 of 453 papers

TitleStatusHype
MTP: Advancing Remote Sensing Foundation Model via Multi-Task PretrainingCode3
RSMamba: Remote Sensing Image Classification with State Space ModelCode3
Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene ClassificationCode2
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
Bridging Remote Sensors with Multisensor Geospatial Foundation ModelsCode2
Few-Shot Scene Classification of Optical Remote Sensing Images Leveraging Calibrated Pretext TasksCode2
VHM: Versatile and Honest Vision Language Model for Remote Sensing Image AnalysisCode2
GeoChat: Grounded Large Vision-Language Model for Remote SensingCode2
RS-Agent: Automating Remote Sensing Tasks through Intelligent AgentCode2
SpectralGPT: Spectral Remote Sensing Foundation ModelCode2
RoMA: Scaling up Mamba-based Foundation Models for Remote SensingCode2
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning PerspectiveCode2
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual TasksCode2
SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote SensingCode2
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial VehiclesCode1
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain ShiftCode1
Decoupling Common and Unique Representations for Multimodal Self-supervised LearningCode1
Debiased Self-Training for Semi-Supervised LearningCode1
Deep CNNs Meet Global Covariance Pooling: Better Representation and GeneralizationCode1
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data AugmentationCode1
CD-COCO: A Versatile Complex Distorted COCO Database for Scene-Context-Aware Computer VisionCode1
Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy EnvironmentsCode1
DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and eventsCode1
BYOL-S: Learning Self-supervised Speech Representations by BootstrappingCode1
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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