Collecting Image Description Datasets using Crowdsourcing

The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags

Crowdsourcing has been emerging to harvest social wisdom from thousands of volunteers to perform series of tasks online. However, little research has been devoted to exploring the impact of various factors such as the content of a resource or crowdsourcing interface design to user tagging behavior. While images’ titles and descriptions are frequently available i...

Collecting Human Habit Datasets for Smart Spaces Through Gamification and Crowdsourcing

Mentor: A Visualization and Quality Assurance Framework for Crowd-Sourced Data Generation

Crowdsourcing is a feasible method for collecting labeled datasets for training and evaluating machine learning models. Compared to the expensive process of generating labeled datasets using dedicated trained judges, the low cost of data generation in crowdsourcing environments enables researchers and practitioners to collect significantly larger amounts of data for the same cost. However, crow...

Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions

The past few years have witnessed renewed interest in NLP tasks at the interface between vision and language. One intensively-studied problem is that of automatically generating text from images. In this paper, we extend this problem to the more specific domain of face description. Unlike scene descriptions, face descriptions are more fine-grained and rely on attributes extracted from the image...

Reliable Task Design for Descriptive Crowdsourcing

Crowdsourcing offers a valuable method to improve information retrieval indexing by using humans to improve the indexable data about documents or entities. Human contributions open the door to latent information, subjective judgments, and other encoding of difficult to extract data. However, such contributions are also subject to variance from the inconsistencies of human interpretation. The pr...