Mikhail Startsev

PhD thesis, 2020

Supersaliency: A Novel Pipeline for Predicting Smooth Pursuit-Based Attention Improves Generalisability of Video Saliency.

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[DOI]

IEEE Access, 2020

2019

A Ground-Truth Data Set and a Classification Algorithm for Eye Movements in 360-degree Videos.

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[DOI]

CoRR, 2019

360-degree Video Gaze Behaviour: A Ground-Truth Data Set and a Classification Algorithm for Eye Movements.

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[DOI]

Proceedings of the 27th ACM International Conference on Multimedia, 2019

Classifying Autism Spectrum Disorder Based on Scanpaths and Saliency.

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[DOI]

Proceedings of the IEEE International Conference on Multimedia & Expo Workshops, 2019

A novel gaze event detection metric that is not fooled by gaze-independent baselines.

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[DOI]

Stefan Göb

Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, 2019

2018

360-aware saliency estimation with conventional image saliency predictors.

[BibT_eX]

[DOI]

Signal Process. Image Commun., 2018

Supersaliency: Predicting Smooth Pursuit-Based Attention with Slicing CNNs Improves Fixation Prediction for Naturalistic Videos.

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[DOI]

CoRR, 2018

Deep learning vs. manual annotation of eye movements.

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[DOI]

Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, 2018

Increasing Video Saliency Model Generalizability by Training for Smooth Pursuit Prediction.

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[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2016

In the pursuit of (ground) truth: a hand-labelling tool for eye movements recorded during dynamic scene viewing.

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[DOI]

Proceedings of the 2016 IEEE Second Workshop on Eye Tracking and Visualization, 2016

Smooth pursuit detection based on multiple observers.

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[DOI]