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.

通过探索简单的视觉传感器在解决视觉任务中的有效性和设计的作用，我们展示了少数光感受器即可解决诸多任务，并通过计算设计优化算法找到了具有良好性能的设计。