Objects are the core meaningful elements in our visual environment. Classic theories of object vision focus upon object recognition and are elegant and simple. Some of their proposals still stand, yet the simplicity is gone. Recent evolutions in behavioral paradigms, neuroscientific methods, and computational modeling have allowed vision scientists to uncover the complexity of the multidimensional representational space that underlies object vision. We review these findings and propose that the key to understanding this complexity is to relate object vision to the full repertoire of behavioral goals that underlie human behavior, running far beyond object recognition. There might be no such thing as core object recognition, and if it exists, then its importance is more limited than traditionally thought.

中文翻译：

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理解人类物体视觉：一张图片胜过一千次表示

对象是我们视觉环境中具有核心意义的元素。经典的物体视觉理论侧重于物体识别，优雅而简单。他们的一些建议仍然有效，但简单性已经不复存在。行为范式、神经科学方法和计算模型的最新发展使视觉科学家能够揭示物体视觉背后的多维表征空间的复杂性。我们回顾了这些发现，并提出理解这种复杂性的关键是将物体视觉与人类行为背后的全部行为目标联系起来，远远超出了物体识别的范围。可能不存在核心物体识别这样的东西，如果它存在，那么它的重要性比传统认为的更有限。