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Datasets/ImageNet-100 (TEMI Split)

ImageNet-100 (TEMI Split)

This split was introduced in TEMI (BMVC 2023)

Adaloglou, Nikolas, Felix Michels, Hamza Kalisch, and Markus Kollmann. "Exploring the Limits of Deep Image Clustering using Pretrained Models." In BMVC. 2023.

Benchmarks

Image Classification/Percentage correctImage Classification/ParamsImage Classification/Novel accuracy (50% Labeled)Image Classification/Seen accuracy (50% Labeled)Image Classification/All accuracy (50% Labeled)Image Classification/All accuracy (10% Labeled)Image Classification/Novel accuracy (10% Labeled)Image Classification/Seen accuracy (10% Labeled)Image Clustering/NMIImage Clustering/ACCURACYImage Clustering/ARISelf-Supervised Learning/Top-1 AccuracySemi-Supervised Image Classification/Novel accuracy (50% Labeled)Semi-Supervised Image Classification/Seen accuracy (50% Labeled)Semi-Supervised Image Classification/All accuracy (50% Labeled)Semi-Supervised Image Classification/All accuracy (10% Labeled)Semi-Supervised Image Classification/Novel accuracy (10% Labeled)Semi-Supervised Image Classification/Seen accuracy (10% Labeled)

Related Benchmarks

ImageNet-100 (Class-IL, 5T)/Image Classification/Top 1 AccuracyImageNet-100 - 50 classes + 10 steps of 5 classes/Incremental Learning/Average Incremental AccuracyImageNet-100 - 50 classes + 25 steps of 2 classes/Incremental Learning/Average Incremental AccuracyImageNet-100 - 50 classes + 5 steps of 10 classes/Incremental Learning/Average Incremental AccuracyImageNet-100 - 50 classes + 5 steps of 10 classes/Object Localization/Average Top-1 localization accuracyImageNet-100 - 50 classes + 50 steps of 1 class/Incremental Learning/Average Incremental Accuracy

Statistics

Papers
12
Benchmarks
18

Links

Tasks

Image ClassificationImage ClusteringOpen-World Semi-Supervised LearningSelf-Supervised LearningSemi-Supervised Image Classification