  Humans are able to perceive, understand and reason about causal events.
Developing models with similar physical and causal understanding capabilities
is a long-standing goal of artificial intelligence. As a step towards this
direction, we introduce CRAFT, a new video question answering dataset that
requires causal reasoning about physical forces and object interactions. It
contains 58K video and question pairs that are generated from 10K videos from
20 different virtual environments, containing various objects in motion that
interact with each other and the scene. Two question categories in CRAFT
include previously studied descriptive and counterfactual questions.
Additionally, inspired by the Force Dynamics Theory in cognitive linguistics,
we introduce a new causal question category that involves understanding the
causal interactions between objects through notions like cause, enable, and
prevent. Our results show that even though the questions in CRAFT are easy for
humans, the tested baseline models, including existing state-of-the-art
methods, do not yet deal with the challenges posed in our benchmark.
