CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions

Tayfun Ates, Muhammed Samil Atesoglu, Cagatay Yigit, Ilker Kesen, Mert Kobas, Erkut Erdem, Aykut Erdem, Tilbe Goksun, Deniz Yuret

Keywords: intuitive physics, visual question answering, force dynamics, causal reasoning, temporal reasoning

TL;DR: We present a new visual question answering dataset named CRAFT, in which working towards an answer requires causal reasoning about physical forces and object interactions.

Abstract: Recent advances in Artificial Intelligence and deep learning have revived the interest in studying the gap between the reasoning capabilities of humans and machines. In this ongoing work, we introduce CRAFT, a new visual question answering dataset that requires causal reasoning about physical forces and object interactions. It contains 38K video and question pairs that are generated from 3K videos from 10 different virtual environments, containing different number of objects in motion that interact with each other. Two question categories from CRAFT include previously studied descriptive and counterfactual questions. Besides, inspired by the theory of force dynamics from the field of human cognitive psychology, we introduce new question categories that involve understanding the intentions of objects through the notions of cause, enable, and prevent. Our preliminary results demonstrate that even though these tasks are very intuitive for humans, the implemented baselines could not cope with the underlying challenges.

Community Implementations: [ 1 code implementation](https://www.catalyzex.com/paper/craft-a-benchmark-for-causal-reasoning-about/code)