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Multi-Duration Saliency Code

Source code for our paper "How Many Glances? Modeling Multi-duration Saliency".

This repo contains models and source code for predicting multi-duration saliency and its applications.

Downloading the CodeCharts1K Dataset

To get started, download the CodeCharts1k multi-duration saliency dataset. Please see the README contained in the CodeCharts1k zip file for a detailed description of its contents.

Performing multi-duration inference

Inference notebook

To perform inference on a few images, we provide the mdsem_simple_inference.ipynb notebook, where our pretrained checkpoints on codecharts and salicon can be loaded and saliency maps can be generated from a few test images.

To run this notebook:

1. Clone the repository
2. Place your test images in the images/ folder.
3. Download the checkpoints from our website (codecharts_checkpoint, salicon-md checkpoint and place them in a folder named ckpt/.
4. Run the notebook.

Important source files

• src/multiduration_models.py: model definitions for multi-duration models.
• src/singleduration_models.py: model definitions for single-duration models.
• src/losses_keras2.py: loss functions used in training
• src/data_loading.py: helper functions to load saliency data sets
• src/eval.py: helper functions for evaluating models on common saliency metrics and saving predictions
• src/util.py: utilities for loading models and losses

Plotting predictions

Use the notebook notebooks/plot_mdsem_predictions.ipynb to plot predictions from MD-SEM.

Multi-duration applications

Please see the applications folder for the source code for our multi-duration saliency applications.

If you want to test out the applications without running the MD-SEM model, you can download the MD-SEM predictions here.