OCTO+: A Suite for Automatic Open-Vocabulary Object Placement in Mixed
  Reality
Aditya Sharma Luke Yoffe Tobias Höllerer
One key challenge in Augmented Reality is the placement of virtual content in
natural locations. Most existing automated techniques can only work with a
closed-vocabulary, fixed set of objects. In this paper, we introduce and
evaluate several methods for automatic object placement using recent advances
in open-vocabulary vision-language models. Through a multifaceted evaluation,
we identify a new state-of-the-art method, OCTO+. We also introduce a benchmark
for automatically evaluating the placement of virtual objects in augmented
reality, alleviating the need for costly user studies. Through this, in
addition to human evaluations, we find that OCTO+ places objects in a valid
region over 70% of the time, outperforming other methods on a range of metrics.