Abstract
The CLEVR dataset has been used extensively in language grounded visual reasoning in Machine Learning (ML) and Natural Language Processing (NLP). We present a graph parser library for CLEVR, that provides functionalities for object-centric attributes and relationships extraction, and construction of structural graph representations for dual modalities. Structural order-invariant representations enable geometric learning and can aid in downstream tasks like language grounding to vision, robotics, compositionality, interpretability, and computational grammar construction. We provide three extensible main components – parser, embedder, and visualizer that can be tailored to suit specific learning setups. We also provide out-of-the-box functionality for seamless integration with popular deep graph neural network (GNN) libraries. Additionally, we discuss downstream usage and applications of the library, and how it can accelerate research for the NLP community.- Anthology ID:
- 2020.nlposs-1.3
- Volume:
- Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Eunjeong L. Park, Masato Hagiwara, Dmitrijs Milajevs, Nelson F. Liu, Geeticka Chauhan, Liling Tan
- Venue:
- NLPOSS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 14–19
- Language:
- URL:
- https://aclanthology.org/2020.nlposs-1.3
- DOI:
- 10.18653/v1/2020.nlposs-1.3
- Cite (ACL):
- Raeid Saqur and Ameet Deshpande. 2020. CLEVR Parser: A Graph Parser Library for Geometric Learning on Language Grounded Image Scenes. In Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), pages 14–19, Online. Association for Computational Linguistics.
- Cite (Informal):
- CLEVR Parser: A Graph Parser Library for Geometric Learning on Language Grounded Image Scenes (Saqur & Deshpande, NLPOSS 2020)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2020.nlposs-1.3.pdf
- Code
- raeidsaqur/clevr-parser
- Data
- CLEVR