Annotation Methodologies for Vision and Language Dataset Creation
This work addresses challenges in dataset annotation for vision and language tasks, but it is incremental as it reviews existing issues without proposing new solutions.
The paper identifies and discusses common difficulties and problems encountered during the creation and validation of annotated vision and language datasets, which are used for tasks like image description generation, action recognition, and visual question answering.
Annotated datasets are commonly used in the training and evaluation of tasks involving natural language and vision (image description generation, action recognition and visual question answering). However, many of the existing datasets reflect problems that emerge in the process of data selection and annotation. Here we point out some of the difficulties and problems one confronts when creating and validating annotated vision and language datasets.