  We apply both a traditional `dropout' approach and a photometric redshift
estimation technique to the Hubble Deep Field South data. We give a list of
dropout selected z$\sim$3 objects, and show their images. We then discuss our
photometric redshift estimation technique, demonstrate both its effectiveness
and the role played by near-IR data, and then apply it to HDF-S to obtain an
estimated redshift distribution.
