English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Gaze estimation is a fundamental task in many applications of computervision, human computer interaction and robotics. Many state-of-the-art methodsare trained and tested on custom datasets, making comparison across methodschallenging. Furthermore, existing gaze estimation datasets have limited headpose and gaze variations, and the evaluations are conducted using differentprotocols and metrics. In this paper, we propose a new gaze estimation datasetcalled ETH-XGaze, consisting of over one million high-resolution images ofvarying gaze under extreme head poses. We collect this dataset from 110participants with a custom hardware setup including 18 digital SLR cameras andadjustable illumination conditions, and a calibrated system to record groundtruth gaze targets. We show that our dataset can significantly improve therobustness of gaze estimation methods across different head poses and gazeangles. Additionally, we define a standardized experimental protocol andevaluation metric on ETH-XGaze, to better unify gaze estimation research goingforward. The dataset and benchmark website are available athttps://ait.ethz.ch/projects/2020/ETH-XGaze

ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation