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1. ResMLP

ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification. It is a simple residual network that alternates (i) a linear layer in which image patches interact, independently and identically across channels, and (ii) a two-layer feed-forward network in which channels interact independently per patch. When trained with a modern training strategy using heavy data-augmentation and optionally distillation, it attains surprisingly good accuracy/complexity trade-offs on ImageNet.

2. VIT

Touvron, Hugo, et al. “Going deeper with image transformers.” arXiv preprint arXiv:2103.17239 (2021).