activity
20072021
most citedMLP-Mixer: An all-MLP Architecture for Vision

1.4k citations · 1.7k across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV2021★ 2 cited

LiT: Zero-Shot Transfer with Locked-image text Tuning

Xiaohua Zhai, Xiao Wang, Basil Mustafa +4

This paper presents contrastive-tuning, a simple method employing contrastive training to align image and text models while still taking advantage of their pre-training. In our emp…

cs.LG2021★ 4 cited

The Impact of Reinitialization on Generalization in Convolutional Neural Networks

Ibrahim Alabdulmohsin, Hartmut Maennel, Daniel Keysers

Recent results suggest that reinitializing a subset of the parameters of a neural network during training can improve generalization, particularly for small training sets. We study…

cs.CV2021

Continental-Scale Building Detection from High Resolution Satellite Imagery

Wojciech Sirko, Sergii Kashubin, Marvin Ritter +7

Identifying the locations and footprints of buildings is vital for many practical and scientific purposes. Such information can be particularly useful in developing regions where a…

cs.LG2021★ 4 cited

A Generalized Lottery Ticket Hypothesis

Ibrahim Alabdulmohsin, Larisa Markeeva, Daniel Keysers +1

We introduce a generalization to the lottery ticket hypothesis in which the notion of "sparsity" is relaxed by choosing an arbitrary basis in the space of parameters. We present ev…

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★ 29 cited

Scaling Vision with Sparse Mixture of Experts

Carlos Riquelme, Joan Puigcerver, Basil Mustafa +5

Sparsely-gated Mixture of Experts networks (MoEs) have demonstrated excellent scalability in Natural Language Processing. In Computer Vision, however, almost all performant network…