RAF-DB (Real-world Affective Faces)
Introduced by Li et al. in Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild
The Real-world Affective Faces Database (RAF-DB) is a dataset for facial expression. It contains 29672 facial images tagged with basic or compound expressions by 40 independent taggers. Images in this database are of great variability in subjects' age, gender and ethnicity, head poses, lighting conditions, occlusions, (e.g. glasses, facial hair or self-occlusion), post-processing operations (e.g. various filters and special effects), etc.
Source: Landmark Guidance Independent Spatio-channel Attention and Complementary Context Information based Facial Expression RecognitionBenchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
RAF-DB
|
S2D
|
|||
|
Real-World Affective Faces
|
Covariance Pooling
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
