DAiSEE is a multi-label video classification dataset comprising of 9,068 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.
Source: DAiSEE: Towards User Engagement Recognition in the WildBenchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
DAiSEE
|
Hybrid EfficientNet B7 + Bi-LSTM
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
