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Multi-layer perceptrons for vision competitive with transformers and CNN

Multi-layer perceptrons for vision competitive with transformers and CNN


MLP is all you need... again? ... MLP-Mixer: An all-MLP Architecture for Vision


MLP-Mixer: An all-MLP Architecture for Vision


A Useful New Image Classification Method That Uses neither CNNs nor Attention


Is MLP Better Than CNN & Transformers For Computer Vision?


GitHub

lucidrains / mlp-mixer-pytorch https://github.com/lucidrains/mlp-mixer-pytorch


... show that while convolutions and attention are both sufficient for good performance, neither of them are necessary.

We present MLP-Mixer, an architecture based exclusively on multi-layer perceptrons (MLPs).

MLP-Mixer contains two types of layers: one with MLPs applied independently to image patches (i.e. "mixing" the per-location features), and one with MLPs applied across patches (i.e. "mixing" spatial information).

When trained on large datasets, or with modern regularization schemes, MLP-Mixer attains competitive scores on image classification benchmarks, with pre-training and inference cost comparable to state-of-the-art models. ...



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