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PyTorch Implementation of SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
This repository contains a PyTorch implementation of SalGAN: Visual Saliency Prediction with Generative Adversarial Networks by Junting Pan et al,. The model learns to predict a saliency map given an input image.
I hope you find this implementation useful.
Results
TODO:
Example Generations
TODO: Predict.ipynb
Training
The code requires a pytorch installation.
Before you train the model, preprocess the dataset by running preprocess.py to resize the ground truth images and saliency maps to 256x192.
To train the model, refer to main.py.
Pretrained Model
TODO:
Data
We used the SALICON dataset for training.