The processing of visual information allows humans, animals, and computer-vision based machines to navigate the world. All visual systems face common challenges when the world rapidly changes. Such changes are often generated by an animal’s own movement. Self-motion for example causes fast changes in illumination and generates global motion patterns on the eye, due to the movement of the world relative to the observer. Diverse visual systems face these common challenges but must also deal with important differences. First, animals experience different environments. Second, animals show different types of behavior, such as walking or flying, and behavior will alter the visual cues that the animal encounters. The goal of AdaptiveVision is to first understand common principles of visual system function, and to then work out how diverse visual systems adapt to specific environmental and behavioral constraints. To achieve this, AdaptiveVision will study two essential visual computations, the robust estimation of contrast in dynamically changing environments, and the encoding of global motion cues generated by self-motion.