SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise

Benchmark Model Rank Results
image-classification-on-cifar-10-with-noisySSR#2Accuracy (under 20% Sym. label noise): 96.74%
image-classification-on-clothing1mSSR#11Accuracy: 74.91
image-classification-on-mini-webvision-1-0SSR#3Top-1 Accuracy: 80.92Top-5 Accuracy: 92.80
learning-with-noisy-labels-on-animalSSR#5Accuracy: 88.5Network: Vgg19-BNImageNet Pretrained: NO