Visual Storytelling
The Visual Storytelling Dataset (VIST) consists of 210,819 unique photos and 50,000 stories. The images were collected from albums on Flickr. The albums included 10 to 50 images and all the images in an album are taken in a 48-hour span. The stories were created by workers on Amazon Mechanical Turk, where the workers were instructed to choose five images from the album and write a story about them. Every story has five sentences, and every sentence is paired with its appropriate image. The dataset is split into 3 subsets, a training set (80%), a validation set (10%) and a test set (10%). All the words and interpunction signs in the stories are separated by a space character and all the location names are replaced with the word location. All the names of people are replaced with the words male or female depending on the gender of the person.
Source: Stories for Images-in-Sequence by using Visual and Narrative Components This research was partially funded by Pendulibrium and the Faculty of computer science and engineering, Ss. Cyril and Methodius University in Skopje.
Image Source: https://arxiv.org/pdf/1604.03968.pdf
Variants: VIST
This dataset is used in 2 benchmarks:
Recent papers with results on this dataset: