  We introduce DAiSEE, the first multi-label video classification dataset
comprising of 9068 video snippets captured from 112 users for recognizing the
user affective states of boredom, confusion, engagement, and frustration in the
wild. The dataset has four levels of labels namely - very low, low, high, and
very high for each of the affective states, which are crowd annotated and
correlated with a gold standard annotation created using a team of expert
psychologists. We have also established benchmark results on this dataset using
state-of-the-art video classification methods that are available today. We
believe that DAiSEE will provide the research community with challenges in
feature extraction, context-based inference, and development of suitable
machine learning methods for related tasks, thus providing a springboard for
further research. The dataset is available for download at
https://people.iith.ac.in/vineethnb/resources/daisee/index.html.
