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This paper provides an overview of the use of causal reasoning in computer vision and machine learning tasks, such as visual comprehension, video understanding, visual-linguistic analysis, and multi-modal fusion. It discusses the challenges of building a strong cognitive model that can fully discover causality and spatial-temporal relations, and provides an overview of the recent advances in causal reasoning for visual tasks.
