  Over the last decade, Computer Vision, the branch of Artificial Intelligence
aimed at understanding the visual world, has evolved from simply recognizing
objects in images to describing pictures, answering questions about images,
aiding robots maneuver around physical spaces and even generating novel visual
content. As these tasks and applications have modernized, so too has the
reliance on more data, either for model training or for evaluation. In this
chapter, we demonstrate that novel interaction strategies can enable new forms
of data collection and evaluation for Computer Vision. First, we present a
crowdsourcing interface for speeding up paid data collection by an order of
magnitude, feeding the data-hungry nature of modern vision models. Second, we
explore a method to increase volunteer contributions using automated social
interventions. Third, we develop a system to ensure human evaluation of
generative vision models are reliable, affordable and grounded in psychophysics
theory. We conclude with future opportunities for Human-Computer Interaction to
aid Computer Vision.
