Group Emotion Recognition on GAF 3.0
90.06AccuracyVE-MD-PersonQuery
Evaluation results
| Method | Links | |
|---|---|---|
| VE-MD-PersonQueryYear=2026, Modalities=Img2026.04 | 90.06 | |
| VE-MD DETRYear=2025, Features=Pred. Body+Face SR, Rank=12026.05 | 90.06 | |
| VE-MD-HeatmapYear=2026, Modalities=Img2026.04 | 89.92 | |
| VE-MD HeatmapYear=2025, Features=Pred. Body+Face SR, Rank=22026.05 | 89.92 | |
| VE-MD HeatmapYear=2025, Features=Pred. Face SR, Rank=32026.05 | 89.6 | |
| VE-MD DETRYear=2025, Features=Pred. Face SR, Rank=42026.05 | 88.29 | |
| VE-MD DETRYear=2025, Features=Pred. Body SR, Rank=52026.05 | 87.99 | |
| CAN, ResNet, SE-NetYear=2018, Modalities=Img2026.04 | 86.9 | |
| CAN, ResNet, SE-NetYear=2018, Ind. Features=Yes, Features=Face, Skeleton, Pose, Rank=62026.05 | 86.9 | |
| PSMFYear=2025, Modalities=Img2026.04 | 83.58 | |
| PSMFYear=2025, Ind. Features=Yes, Features=Face, Scene, Rank=72026.05 | 83.58 | |
| Graph-based Prototype Network SubgraphAuthors=Huang et al. [99], Methodology=Graph-based Prototype Network Subgraph2026.05 | 83.58 | |
| DenseNet, SphereFaceYear=2018, Ind. Features=Yes, Features=Face, Skeleton, Rank=82026.05 | 80.98 | |
| ResNet, VGGYear=2018, Ind. Features=Yes, Features=Face, Skeleton, Rank=92026.05 | 78.39 |