  A de facto standard in solving computer vision problems is to use a common
high-resolution camera and choose its placement on an agent (i.e., position and
orientation) based on human intuition. On the other hand, extremely simple and
well-designed visual sensors found throughout nature allow many organisms to
perform diverse, complex behaviors. In this work, motivated by these examples,
we raise the following questions: 1. How effective simple visual sensors are in
solving vision tasks? 2. What role does their design play in their
effectiveness? We explore simple sensors with resolutions as low as one-by-one
pixel, representing a single photoreceptor First, we demonstrate that just a
few photoreceptors can be enough to solve many tasks, such as visual navigation
and continuous control, reasonably well, with performance comparable to that of
a high-resolution camera. Second, we show that the design of these simple
visual sensors plays a crucial role in their ability to provide useful
information and successfully solve these tasks. To find a well-performing
design, we present a computational design optimization algorithm and evaluate
its effectiveness across different tasks and domains, showing promising
results. Finally, we perform a human survey to evaluate the effectiveness of
intuitive designs devised manually by humans, showing that the computationally
found design is among the best designs in most cases.
