  We search for the Baryon Acoustic Oscillations in the projected
cross-correlation function binned into transverse comoving radius between the
SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected
from the DESI Legacy Imaging Surveys. We estimate the density of the
photometric sample of galaxies in this redshift range to be about 2900
deg$^{-2}$, which is deeper than the official DESI ELG selection, and the
density of the spectroscopic sample is about 20 deg$^{-2}$. In order to
mitigate the systematics related to the use of different imaging surveys close
to the detection limit, we use a neural network approach that accounts for
complex dependencies between the imaging attributes and the observed galaxy
density. We find that we are limited by the depth of the imaging surveys which
affects the density and purity of the photometric sample and its overlap in
redshift with the quasar sample, which thus affects the performance of the
method. When cross-correlating the photometric galaxies with quasars in $0.6
\leq z \leq 1.2$, the cross-correlation function can provide better constraints
on the comoving angular distance, $D_{\rm M}$ (6\% precision) compared to the
constraint on the spherically-averaged distance $D_{\rm V}$ (9\% precision)
obtained from the auto-correlation. Although not yet competitive, this
technique will benefit from the arrival of deeper photometric data from
upcoming surveys which will enable it to go beyond the current limitations we
have identified in this work.
