adversarial-network-for-conditioned-feature-generation
adversarial-network-for-conditioned-feature-generation copied to clipboard
nikhil-dce
Zero-Shot Learning using GAN
Adversarial Feature Generation for Zero-Shot Learning
We try to generate synthetic data for unseen classes conditioned on class attributes. Training is done using wasserstein generative adversarial network.
Architecture Diagram
Loss Function
Train
python train.py --logdir run_dir --train-dir /data/CUBNew
Parameters:
- iterations
- batch_size
- dropout
- train_dir
- logdir
- z_dim
- g_steps
- d_steps
- lr
- wgan
- log_interval
Results
Data
Link - (https://drive.google.com/file/d/1XIFik0Cv1MTWtQEQQUZygOwL-X-ZajKY/view?usp=sharing)
nikhil-dce