Multi-Task Self-Training for Learning General Representations-Reference-Cited by-同舟云学术

Multi-Task Self-Training for Learning General Representations

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Ghiasi Golnaz¹,Zoph Barret¹,Cubuk Ekin D.¹,Le Quoc V.¹,Lin Tsung-Yi¹

Affiliation:

1. Google Research,Brain Team

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710361.pdf?arnumber=9710361

Reference62 articles.

1. Exploring the limits of transfer learning with a unified text-to-text transformer;raffel;JMLR,2020

2. Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases;purushwalkam,2020

3. Feature Pyramid Networks for Object Detection

4. An analysis of pre-training on object detection;li;CoRR,2019

5. Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks;lee;Workshop on Challenges in Representation Learning,2013

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