Videos often capture objects, their visible properties, their motion, and the
interactions between different objects. Objects also have physical properties
such as mass, which the imaging pipeline is unable to directly capture.
However, these properties can be estimated by utilizing cues from relative
object motion and the dynamics introduced by collisions. In this paper, we
introduce CRIPP-VQA, a new video question answering dataset for reasoning about
the implicit physical properties of objects in a scene. CRIPP-VQA contains
videos of objects in motion, annotated with questions that involve
counterfactual reasoning about the effect of actions, questions about planning
in order to reach a goal, and descriptive questions about visible properties of
objects. The CRIPP-VQA test set enables evaluation under several
out-of-distribution settings -- videos with objects with masses, coefficients
of friction, and initial velocities that are not observed in the training
distribution. Our experiments reveal a surprising and significant performance
gap in terms of answering questions about implicit properties (the focus of
this paper) and explicit properties of objects (the focus of prior work).

介绍了 CRIPP-VQA 数据集，该数据集包含具有物理性质的场景中物体运动的视频并配有各种类型的问题，强调了隐含属性问题和明确属性问题的巨大性能差距。