Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields

Benchmark Model Rank Results
image-classification-on-stanford-carsViT-B/16 (RPE w/ GAB)#7Accuracy: 93.743
image-classification-on-stanford-carsViT-M/16 (RPE w/ GAB)#20Accuracy: 83.89
fine-grained-image-classification-on-caltech-101ViT-S/16 (RPE w/ GAB)#11Top-1 Error Rate: 9.798%
fine-grained-image-classification-on-stanford-dogsViT-B/16 (RPE w/ GAB)#13Accuracy: 90.185%
semantic-segmentation-on-ade20k-valSwin-S (RPE w/ GAB)#65mIoU: 46.41
object-detection-on-coco-test-devSwin-S (RPE w/ GAB)#100box mAP: 48.23
image-classification-on-imagenetViT-B/16 (RPE w/ GAB)#677Top 1 Accuracy: 81.484%