Papers › GReFEL: Geometry-Aware Reliable Facial Expression Learning under Bias and Imbalanced...
GReFEL: Geometry-Aware Reliable Facial Expression Learning under Bias and Imbalanced Data Distribution
Azmine Toushik Wasi, Taki Hasan Rafi, Raima Islam, Karlo Serbetar, Dong Kyu Chae
Reliable facial expression learning (FEL) involves the effective learning of distinctive facial expression characteristics for more reliable, unbiased and accurate predictions in real-life settings. However, current systems struggle with FEL tasks because of the variance in people's facial expressions due to their unique facial structures, movements, tones, and demographics. Biased and imbalanced datasets compound this challenge, leading to wrong and biased prediction labels. To tackle these, we introduce GReFEL, leveraging Vision Transformers and a facial geometry-aware anchor-based reliability balancing module to combat imbalanced data distributions, bias, and uncertainty in facial expression learning. Integrating local and global data with anchors that learn different facial data points and structural features, our approach adjusts biased and mislabeled emotions caused by intra-class disparity, inter-class similarity, and scale sensitivity, resulting in comprehensive, accurate, and reliable facial expression predictions. Our model outperforms current state-of-the-art methodologies, as demonstrated by extensive experiments on various datasets.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Facial Expression Recognition (FER) | Aff-Wild2 | GReFEL | Accuracy | 72.48 | #1 of 2 | Archive leaderboard | report |
| Facial Expression Recognition (FER) | FER+ | GReFEL | Accuracy | 93.09 | #2 of 14 | Archive leaderboard | report |
| Facial Expression Recognition (FER) | FERG | GReFEL | Accuracy | 98.18 | #2 of 2 | Archive leaderboard | report |
| Facial Expression Recognition (FER) | JAFFE | GReFEL | Accuracy | 96.67 | #2 of 4 | Archive leaderboard | report |
| Facial Expression Recognition (FER) | RAF-DB | GReFEL | Overall Accuracy | 92.47 | #7 of 35 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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