Dear colleague,

It is our pleasure to announce to you that we have joined hands with Facebook Reality Labs to organize a joint full-day workshop at ECCV 2020 in Glasgow, UK. Specifically, this is an event combining the former OpenEDS workshop (organized by Facebook at ICCV 2019) and our GAZE workshop. In this way, we will be able to cover a broader range of topics involving eye-tracking, including the context of AR/VR as well as in natural settings.

The workshop will host two tracks: the first focuses on gaze estimation and prediction methods, with a focus on accuracy and robustness in natural settings (in-the-wild); the second track focuses on the scale and generalization problem for eye-tracking systems operating on AR and VR platforms. The second track also includes the 2020 eye-tracking challenge. More information on the OpenEDS 2020 challenge can be found at https://research.fb.com/programs/openeds-2020-challenge/

The webpage for the new workshop can be found at: https://openeyes-workshop.github.io/

and the following topics are of particular interest to us this year:

• Proposal of novel eye detection, gaze estimation pipelines using deep neural networks that incorporate one or all of the following:
• Geometric/anatomical constraints into the network in a differentiable manner.
• Demonstration of robustness to conditions where current methods fail (illumination, appearance, low-resolution etc.).
• Robust estimation from different data modalities such as RGB, depth, and near IR.
• Use of additional cues, such as task context, temporal data, eye movement classification.
• Designing new, accurate metrics to account for rapid eye movements in the real world.
• Semi-/un-/self-supervised learning, meta-learning, domain adaptation, attention mechanisms and other related machine learning methods for gaze estimation.
• Methods for temporal gaze estimation and prediction including Bayesian methods.
• Unsupervised semantic segmentation of eye regions.
• Active learning frameworks for semantic segmentation of eye images.
• Generative models for eye image synthesis and gaze estimation.
• Transfer learning for eye tracking from simulation data to real data.
• Domain transfer applications for eye tracking.

This workshop will accept submissions of both published and unpublished works. We will also solicit high-quality eye tracking-related papers rejected at ECCV 2020, accompanied by the reviews and a letter of changes which clearly states the changes made to address comments by the previous reviewers. Accepted papers may be featured as spotlight talks and posters. In addition to regular workshop papers, we also invite extended abstracts of ongoing or published work (e.g. related papers on ECCV main track). We see this as an opportunity for authors to promote their work to an interested audience. Extended abstracts are limited to six pages (excluding references).