Multilingual Image Corpus: Annotation Protocol

Svetla Koeva


Abstract
In this paper, we present work in progress aimed at the development of a new image dataset with annotated objects. The Multilingual Image Corpus consists of an ontology of visual objects (based on WordNet) and a collection of thematically related images annotated with segmentation masks and object classes. We identified 277 dominant classes and 1,037 parent and attribute classes, and grouped them into 10 thematic domains such as sport, medicine, education, food, security, etc. For the selected classes a large-scale web image search is being conducted in order to compile a substantial collection of high-quality copyright free images. The focus of the paper is the annotation protocol which we established to facilitate the annotation process: the Ontology of visual objects and the conventions for image selection and for object segmentation. The dataset is designed both for image classification and object detection and for semantic segmentation. In addition, the object annotations will be supplied with multilingual descriptions by using freely available wordnets.
Anthology ID:
2021.ranlp-1.80
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
Month:
September
Year:
2021
Address:
Held Online
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
701–707
Language:
URL:
https://aclanthology.org/2021.ranlp-1.80
DOI:
Bibkey:
Cite (ACL):
Svetla Koeva. 2021. Multilingual Image Corpus: Annotation Protocol. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 701–707, Held Online. INCOMA Ltd..
Cite (Informal):
Multilingual Image Corpus: Annotation Protocol (Koeva, RANLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.ranlp-1.80.pdf
Data
COCOCaltech-256ImageNetLabelMeModaNetSilhouettesTiny Images