Do we understand high-level vision?

'High-level' vision lacks a single, agreed upon definition, but it might usefully be defined as those stages of visual processing that transition from analyzing local image structure to analyzing structure of the external world that produced those images. Much work in the last several decades has focused on object recognition as a framing problem for the study of high-level visual cortex, and much progress has been made in this direction. This approach presumes that the operational goal of the visual system is to read-out the identity of an object (or objects) in a scene, in spite of variation in the position [1], size [2], lighting [3] and the presence of other nearby objects [4,5]. However, while object recognition as a operational framing of high-level is intuitive appealing, it is by no means the only task that visual cortex might do, and the study of object recognition is beset by challenges in building stimulus sets that adequately sample the infinite space of possible stimuli. Here I review the successes and limitations of this work, and ask whether we should reframe our approaches to understanding high-level vision.