Awesome

Counterfactual Zero-Shot and Open-Set Visual Recognition

This project provides implementations for our CVPR 2021 paper Counterfactual Zero-Shot and Open-Set Visual Recognition, where we propose a counterfactual-based binary seen/unseen classifier (GCM-CF) for Zero-Shot Learning (ZSL) and Open-Set Recognition (OSR). This repo contains

• ZSL: Strong binary seen/unseen classifier that is plug-and-play with any ZSL method
• ZSL: Integrations with TF-VAEGAN, RelationNet, GDAN, CADA-VAE, LisGAN, AREN
• OSR: Complete the OSR code base on MNIST, SVHN, CIFAR10, CIFAR+10, CIFAR+50 with 5 fixed random seed
• OSR: Strong baseline (F1 score) of Softmax, OpenMax, CGDL
• OSR: Implementation of our GCM-CF

Counterfactual Zero-Shot and Open-Set Visual Recognition <br /> Zhongqi Yue*, Tan Wang*, Hanwang Zhang, Qianru Sun, Xian-Sheng Hua <br /> * Equal contribution <br /> IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 <br />

Usage

Please refer to the README.md in ZSL and OSR folder, respectively.

TODO

Citation

If you find our work or the code useful, please consider cite our paper using:

@inproceedings{yue2021counterfactual,
  title={Counterfactual Zero-Shot and Open-Set Visual Recognition},
  author={Yue, Zhongqi and Wang, Tan and Zhang, Hanwang and Sun, Qianru and Hua, Xian-Sheng},
  booktitle= {CVPR},
  year={2021}
}