Abstract: The interaction properties between actors and the surrounding environment are studied by Affordance understanding based on computer vision, which is significant in the fields of robot navigation and grasping. Therefore, the current research status of computer vision-based Affordance understanding was comprehensively reviewed. First, the methods proposed in recent years were classified according to the research direction, and the ideas and characteristics of different methods were synthesized. Then, several public datasets were introduced, and the performance of different methods on these datasets was comparatively analyzed. Finally, the advantages and disadvantages of various methods in computer vision-based Affordance understanding and future development trends were expounded.