This repository holds the code for the paper.
ComPhy: Compositional Physical Reasoning ofObjects and Events from Videos, (ICLR 2022)
git clone https://github.com/comphyreasoning/compositional_physics_learner.git
pip install -r requirements
- Download videos, video annotation, questions from the project website.
- Download the regional proposals with attribute and physical property prediction from the anonymous Google drive
- Download the dynamic predictions from the anonymous Google drive
- Run executor for factual questions.
sh scripts/test_oe_release.sh
- Run executor for multiple-choice questions.
sh scripts/test_mc_release.sh
- Submit results onto the evaluation server.
Please refer to this repo for property learning and dynamics prediction.
This module uses the public NS-VQA's perception module object detection and visual attribute extraction.
This module uses the public NS-VQA's program parser module to tranform language into executable programs.