I need to train a neural net classifier for different types of eye movements, and there seems very little data available on this.

quick web search gives handful of resources

http://saliency.mit.edu/datasets.html

This was the first data set with held-out human eye movements, and is used as a benchmark test set. eyetracker: ETL 400 ISCAN (240Hz)

or

This dataset contains two sets of images: train and test. Train images (100 from each category) and fixations of 18 observers are shared but 6 observers are held-out. Test images are available but fixations of all 24 observers are held out. eyetracker: EyeLink1000 (1000Hz)

http://gazecapture.csail.mit.edu and https://github.com/CSAILVision/GazeCapture

In the dataset, we include data for 1474 unique subjects. Each numbered directory represents a recording session from one of those subjects. Numbers were assigned sequentially, although some numbers are missing for various reasons (e.g., test recordings, duplicate subjects, or incomplete uploads).

http://calvin.inf.ed.ac.uk/datasets/poet-dataset/

We collected eye tracking data for the complete trainval set of ten objects classes (cat, dog, bicycle, motorbike, boat, aeroplane, horse, cow, sofa, diningtable) from Pascal VOC 2012 [2] (6,270 images in total). Each image is annotated with the eye movement record of five participants, whose task was to identify which object class was present in the image.

etc

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