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Datasets/Stanford Cars

Stanford Cars

ImagesCustom (non-commercial)Introduced 2017-02-06

The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear. The data is divided into almost a 50-50 train/test split with 8,144 training images and 8,041 testing images. Categories are typically at the level of Make, Model, Year. The images are 360×240.

Source: View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network Image Source: https://ai.stanford.edu/~jkrause/cars/car_dataset.html

Benchmarks

AutoML/Accuracy (%)AutoML/FLOPSAutoML/PARAMSClassification/Recall@1Classification/Recall@2Classification/Recall@5Classification/Recall@10Few-Shot Learning/4-shot AccuracyFew-Shot Learning/8-shot AccuracyFew-Shot Learning/12-shot AccuracyFew-Shot Learning/16-shot AccuracyFine-Grained Image Classification/AccuracyFine-Grained Image Classification/FLOPSFine-Grained Image Classification/PARAMSImage Classification/AccuracyImage Classification/FLOPSImage Classification/PARAMSImage Clustering/AccuracyImage Clustering/NMIImage Generation/FIDImage Generation/Inception scoreMeta-Learning/4-shot AccuracyMeta-Learning/8-shot AccuracyMeta-Learning/12-shot AccuracyMeta-Learning/16-shot AccuracyNeural Architecture Search/Accuracy (%)Neural Architecture Search/FLOPSNeural Architecture Search/PARAMSPrompt Engineering/Harmonic meanZero-Shot Learning/Accuracy

Related Benchmarks

Stanford Cars (Fine-grained 6 Tasks)/Continual Learning/AccuracyStanford Cars 5-way (1-shot)/Few-Shot Image Classification/AccuracyStanford Cars 5-way (1-shot)/Image Classification/AccuracyStanford Cars 5-way (5-shot)/Few-Shot Image Classification/AccuracyStanford Cars 5-way (5-shot)/Image Classification/Accuracy

Statistics

Papers
790
Benchmarks
30

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AutoMLClassificationContinual LearningFew-Shot Image ClassificationFew-Shot LearningFew-Shot Learning - 4 shotsFine-Grained Image ClassificationImage ClassificationImage ClusteringImage GenerationLearning with coarse labelsMeta-LearningNeural Architecture SearchPrompt EngineeringTransductive Zero-Shot ClassificationZero-Shot Learning