BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning

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Benchmark Model Rank Results
long-tail-learning-on-inaturalist-2018BatchFormer(ResNet-50, RIDE)#19Top-1 Accuracy: 74.1%
long-tail-learning-on-cifar-100-lt-r-100Paco + BatchFormer#22Error Rate: 47.6
long-tail-learning-on-cifar-100-lt-r-100Balanced + BatchFormer#23Error Rate: 48.3
domain-generalization-on-pacsBatchFormer(ResNet-50, SWAD)#23Average Accuracy: 88.6
long-tail-learning-on-imagenet-ltBatchFormer(ResNet-50, PaCo)#29Top-1 Accuracy: 57.4
long-tail-learning-on-imagenet-ltBatchFormer(ResNet-50, RIDE)#36Top-1 Accuracy: 55.7

Rank counts only results with a code link.