SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning

16 September 2020

Papers citing "SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning"

9 / 9 papers shown

Title
Which Model to Transfer? Finding the Needle in the Growing Haystack Cédric Renggli André Susano Pinto Luka Rimanic J. Puigcerver C. Riquelme Ce Zhang Mario Lucic 46 25 0 13 Oct 2020
Scalable Transfer Learning with Expert Models J. Puigcerver C. Riquelme Basil Mustafa Cédric Renggli André Susano Pinto Sylvain Gelly Daniel Keysers N. Houlsby 97 63 0 28 Sep 2020
What Makes for Good Views for Contrastive Learning? Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid Phillip Isola SSL 56 1,313 0 20 May 2020
Are Labels Necessary for Neural Architecture Search? Chenxi Liu Piotr Dollár Kaiming He Ross B. Girshick Alan Yuille Saining Xie 36 75 0 26 Mar 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 405 3,397 0 09 Mar 2020
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules Daniel Ho Eric Liang Ion Stoica Pieter Abbeel Xi Chen 46 402 0 14 May 2019
Revisiting Self-Supervised Visual Representation Learning Alexander Kolesnikov Xiaohua Zhai Lucas Beyer SSL 110 716 0 25 Jan 2019
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 183 15,825 0 12 Nov 2013
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell VLM ObjD 105 4,946 0 06 Oct 2013