  Automatically describing images using natural sentences is an important task
to support visually impaired people's inclusion onto the Internet. It is still
a big challenge that requires understanding the relation of the objects present
in the image and their attributes and actions they are involved in. Then,
visual interpretation methods are needed, but linguistic models are also
necessary to verbally describe the semantic relations. This problem is known as
Image Captioning. Although many datasets were proposed in the literature, the
majority contains only English captions, whereas datasets with captions
described in other languages are scarce. Recently, a movement called PraCegoVer
arose on the Internet, stimulating users from social media to publish images,
tag #PraCegoVer and add a short description of their content. Thus, inspired by
this movement, we have proposed the #PraCegoVer, a multi-modal dataset with
Portuguese captions based on posts from Instagram. It is the first large
dataset for image captioning in Portuguese with freely annotated images.
Further, the captions in our dataset bring additional challenges to the
problem: first, in contrast to popular datasets such as MS COCO Captions,
#PraCegoVer has only one reference to each image; also, both mean and variance
of our reference sentence length are significantly greater than those in the MS
COCO Captions. These two characteristics contribute to making our dataset
interesting due to the linguistic aspect and the challenges that it introduces
to the image captioning problem. We publicly-share the dataset at
https://github.com/gabrielsantosrv/PraCegoVer.
