Skip to content
/ GLoFA Public

This is the code of AAAI'21 paper "Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors".

License

Notifications You must be signed in to change notification settings

njulus/GLoFA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

GLoFA

This is the code of AAAI 2021 paper "Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors". If you use any content of this repo for your work, please cite the following bib entry:

@inproceedings{lu2021glofa,
  author    = {Su Lu and
               Han-Jia Ye and
               De-Chuan Zhan},
  title     = {Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  pages     = {8776--8783},
  year      = {2021}
}

Pretrained Models

Pretrained weights of ResNet-12 and ConvNet can be downloaded at https://github.com/Sha-Lab/FEAT.

About

This is the code of AAAI'21 paper "Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors".

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages