Edit Social Preview


Upload an image to customize your repository’s social media preview.
Images should be at least 640×320px (1280×640px for best display).

DAiSEE: Towards User Engagement Recognition in the Wild

7 Sep 2016 • Abhay Gupta • Arjun D'Cunha • Kamal Awasthi • Vineeth Balasubramanian

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... (read more)

PDF Abstract

Code
Add Remove Mark official

No code implementations yet. Submit your code now

Tasks
Add Remove

Datasets

Introduced in the Paper:

DAiSEE

Mentioned in the Paper:

ImageNet COCO CK+ VGG Face

Results from the Paper
Edit

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper
Add Remove

METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet
Contact us on: hello@paperswithcode.com . Papers With Code is a free resource with all data licensed under CC-BY-SA.
Terms Privacy Cookies policy