Static Facial Expression in the Wild
The Static Facial Expressions in the Wild (SFEW) dataset is a dataset for facial expression recognition. It was created by selecting static frames from the AFEW database by computing key frames based on facial point clustering. The most commonly used version, SFEW 2.0, was the benchmarking data for the SReco sub-challenge in EmotiW 2015. SFEW 2.0 has been divided into three sets: Train (958 samples), Val (436 samples) and Test (372 samples). Each of the images is assigned to one of seven expression categories, i.e., anger, disgust, fear, neutral, happiness, sadness, and surprise. The expression labels of the training and validation sets are publicly available, whereas those of the testing set are held back by the challenge organizer.
Source: Deep Facial Expression Recognition: A Survey
Image Source: https://computervisiononline.com/dataset/1105138659
Variants: SFEW
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Facial Expression Recognition (FER) | ViT + SE | Learning Vision Transformer with Squeeze … | 2021-07-07 |
| Facial Expression Recognition (FER) | RAN (VGG16+ResNet18) | Region Attention Networks for Pose … | 2019-05-10 |
| Facial Expression Recognition (FER) | Island Loss | Island Loss for Learning Discriminative … | 2017-10-09 |
Recent papers with results on this dataset: