activity
20162021
most citedAn Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

22k citations · 25.2k across the 19 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2021

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations

Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot +10

A classical problem in computer vision is to infer a 3D scene representation from few images that can be used to render novel views at interactive rates. Previous work focuses on r…

cs.CV2021★ 1.4k cited

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…

cs.CV2021★ 54 cited

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai +3

Vision Transformers (ViT) have been shown to attain highly competitive performance for a wide range of vision applications, such as image classification, object detection and seman…

cs.CV2021

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…

cs.CV2020★ 22k cited

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov +9

While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention…

cs.CV2019★ 14 cited

Scaling Autoregressive Video Models

Dirk Weissenborn, Oscar Täckström, Jakob Uszkoreit

Due to the statistical complexity of video, the high degree of inherent stochasticity, and the sheer amount of data, generating natural video remains a challenging task. State-of-t…

cs.CV2018★ 227 cited

Image Transformer

Niki Parmar, Ashish Vaswani, Jakob Uszkoreit +4

Image generation has been successfully cast as an autoregressive sequence generation or transformation problem. Recent work has shown that self-attention is an effective way of mod…