22k citations · 31.6k across the 22 of their papers we have counts for
4 papers · 1 filter
Do Vision Transformers See Like Convolutional Neural Networks?
Maithra Raghu, Thomas Unterthiner, Simon Kornblith +2
Convolutional neural networks (CNNs) have so far been the de-facto model for visual data. Recent work has shown that (Vision) Transformer models (ViT) can achieve comparable or eve…
MLP-Mixer: An all-MLP Architecture for Vision
Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov +9
Convolutional Neural Networks (CNNs) are the go-to model for computer vision. Recently, attention-based networks, such as the Vision Transformer, have also become popular. In this…
Differentiable Patch Selection for Image Recognition
Jean-Baptiste Cordonnier, Aravindh Mahendran, Alexey Dosovitskiy +3
Neural Networks require large amounts of memory and compute to process high resolution images, even when only a small part of the image is actually informative for the task at hand…
Understanding Robustness of Transformers for Image Classification
Srinadh Bhojanapalli, Ayan Chakrabarti, Daniel Glasner +3
Deep Convolutional Neural Networks (CNNs) have long been the architecture of choice for computer vision tasks. Recently, Transformer-based architectures like Vision Transformer (Vi…