Datasets for the proposed challenge are available. The MiGA challenge is planned as a continuous annual event. Two benchmark datasets published on IJCV 2023 and CVPR 2021 are available and will be used for the challenge. The first one is the SMG dataset published in IJCV 2023. The spontaneous Micro-Gesture (SMG) dataset consists of 3,692 samples of 17 MGs. The MG clips are annotated from 40 long video sequences (10-15 minutes) with 821,056 frames in total. The datasets were collected from 40 subjects while narrating a fake and real story to elicit emotional states. The participants are recorded and collected by Kinect resulting in four modalities, RGB, 3D skeletal joints, depth and silhouette. In this workshop, we allow participants to use the skeleton, RGB or both modalities. [Download SMG dataset](https://www.oulu.fi/en/university/faculties-and-units/faculty-information-technology-and-electrical-engineering/center-machine-vision-and-signal-analysis)

The second dataset is iMiGUE published in CVPR2021. Micro-Gesture Understanding and Emotion analysis (iMiGUE) dataset consists of 32 MGs plus one non-MG class collected from post-match press conferences videos of famous tennis players. The dataset consists of 18,499 samples of MGs to detect negative and positive emotions. The MG clips are annotated from 359 long video sequences (0.5-26 minutes) with 3,765,600 frames in total. The dataset contains RGB modality and 2D skeletal joints collected from Open-Pose. In this workshop, we allow participants to use the skeleton, RGB or both modalities. [Download iMiGUE dataset](https://www.oulu.fi/en/university/faculties-and-units/faculty-information-technology-and-electrical-engineering/center-machine-vision-and-signal-analysis)

**The training and validation sets (skeleton + RGB modality) of the iMiGUE and SMG datasets will released for the competition on April 9th.**