  The Exoplanet Imaging Data Challenge is a community-wide effort meant to
offer a platform for a fair and common comparison of image processing methods
designed for exoplanet direct detection. For this purpose, it gathers on a
dedicated repository (Zenodo), data from several high-contrast ground-based
instruments worldwide in which we injected synthetic planetary signals. The
data challenge is hosted on the CodaLab competition platform, where
participants can upload their results. The specifications of the data challenge
are published on our website. The first phase, launched on the 1st of September
2019 and closed on the 1st of October 2020, consisted in detecting point
sources in two types of common data-set in the field of high-contrast imaging:
data taken in pupil-tracking mode at one wavelength (subchallenge 1, also
referred to as ADI) and multispectral data taken in pupil-tracking mode
(subchallenge 2, also referred to as ADI mSDI). In this paper, we describe the
approach, organisational lessons-learnt and current limitations of the data
challenge, as well as preliminary results of the participants submissions for
this first phase. In the future, we plan to provide permanent access to the
standard library of data sets and metrics, in order to guide the validation and
support the publications of innovative image processing algorithms dedicated to
high-contrast imaging of planetary systems.
