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

Showing 1120 of 453 papers

TitleStatusHype
SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote SensingCode2
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
GeoChat: Grounded Large Vision-Language Model for Remote SensingCode2
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning PerspectiveCode2
ApproxDet: Content and Contention-Aware Approximate Object Detection for MobilesCode1
APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIPCode1
Debiased Self-Training for Semi-Supervised LearningCode1
Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy EnvironmentsCode1
APLA: A Simple Adaptation Method for Vision TransformersCode1
DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and eventsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100Unverified
2AGOSAccuracy (%)99.88Unverified
3LSE-NetAccuracy (%)99.78Unverified
4ResNet50Accuracy (%)99.61Unverified
5MSMatchAccuracy (%)98.33Unverified
6MIDC-NetAccuracy (%)97.4Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68Unverified
2WaveMixTop 1 Error43.55Unverified