Spatiotemporal Facial Action Unit Detection using Twin Cycle Autoencoders for Driver Monitoring
Driver monitoring systems (DMS) increasingly rely on facial cues to infer drowsiness, distraction, and cognitive load in real time. Facial Action Units (AUs), grounded in the Facial Action Coding System (FACS), provide an objective and interpretable representation of such states, but their automatic detection in the driving context is complicated by low and variable illumination, partial occlusion, head-pose variation, and the subtlety and short duration of relevant AU activations. Existing AU detectors largely treat spatial appearance and temporal dynamics separately, limiting their ability to exploit self-supervisory signal from abundant unlabeled driving video. We propose the Twin Cycl...
| Authors | Sai Sidharth D |
|---|---|
| Primary category | cs.CV |
| Published | 18 July 2026 |
| Last updated at source | 22 July 2026 |
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