Decoding Language Spatial Relations to 2D Spatial Arrangements

Gorjan Radevski, Guillem Collell, Marie-Francine Moens, Tinne Tuytelaars


Abstract
We address the problem of multimodal spatial understanding by decoding a set of language-expressed spatial relations to a set of 2D spatial arrangements in a multi-object and multi-relationship setting. We frame the task as arranging a scene of clip-arts given a textual description. We propose a simple and effective model architecture Spatial-Reasoning Bert (SR-Bert), trained to decode text to 2D spatial arrangements in a non-autoregressive manner. SR-Bert can decode both explicit and implicit language to 2D spatial arrangements, generalizes to out-of-sample data to a reasonable extent and can generate complete abstract scenes if paired with a clip-arts predictor. Finally, we qualitatively evaluate our method with a user study, validating that our generated spatial arrangements align with human expectation.
Anthology ID:
2020.findings-emnlp.408
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4549–4560
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.408
DOI:
10.18653/v1/2020.findings-emnlp.408
Bibkey:
Cite (ACL):
Gorjan Radevski, Guillem Collell, Marie-Francine Moens, and Tinne Tuytelaars. 2020. Decoding Language Spatial Relations to 2D Spatial Arrangements. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4549–4560, Online. Association for Computational Linguistics.
Cite (Informal):
Decoding Language Spatial Relations to 2D Spatial Arrangements (Radevski et al., Findings 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.findings-emnlp.408.pdf
Optional supplementary material:
 2020.findings-emnlp.408.OptionalSupplementaryMaterial.zip
Video:
 https://slideslive.com/38940092
Code
 gorjanradevski/sr-bert