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20172022
most citedStand-Alone Self-Attention in Vision Models

221 citations · 746 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV202115 cited

Revisiting 3D ResNets for Video Recognition

Xianzhi Du, Yeqing Li, Yin Cui +3

A recent work from Bello shows that training and scaling strategies may be more significant than model architectures for visual recognition. This short note studies effective train…

cs.CV2021210 cited

Revisiting ResNets: Improved Training and Scaling Strategies

Irwan Bello, William Fedus, Xianzhi Du +5

Novel computer vision architectures monopolize the spotlight, but the impact of the model architecture is often conflated with simultaneous changes to training methodology and scal…

cs.CV202148 cited

LambdaNetworks: Modeling Long-Range Interactions Without Attention

Irwan Bello

We present lambda layers -- an alternative framework to self-attention -- for capturing long-range interactions between an input and structured contextual information (e.g. a pixel…

cs.CV2020

Global Self-Attention Networks for Image Recognition

Zhuoran Shen, Irwan Bello, Raviteja Vemulapalli +2

Recently, a series of works in computer vision have shown promising results on various image and video understanding tasks using self-attention. However, due to the quadratic compu…

cs.CV2019221 cited

Stand-Alone Self-Attention in Vision Models

Prajit Ramachandran, Niki Parmar, Ashish Vaswani +3

Convolutions are a fundamental building block of modern computer vision systems. Recent approaches have argued for going beyond convolutions in order to capture long-range dependen…

cs.CV2019

Attention Augmented Convolutional Networks

Irwan Bello, Barret Zoph, Ashish Vaswani +2

Convolutional networks have been the paradigm of choice in many computer vision applications. The convolution operation however has a significant weakness in that it only operates…