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Research map / Label-efficient and robust learning / Recognition and long-tail

Deep Region and Multi-Label Learning for Facial Action Unit Detection

CVPR 2016 · Label-efficient and robust learning › Recognition and long-tail · approach: Loss design and classifier theory · 342 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use DRML instead of JPMLAU detection · BP4DF1-frame (Avg.): 45.9 -> 48.3Helped
Use DRML instead of LCNAU detection · BP4DAUC (Avg.): 54.4 -> 56.0Helped
Use DRML instead of LCNAU detection · DISFAF1-frame (Avg.): 24.0 -> 26.7Helped
Use DRML instead of AlexNetAU detection · DISFAAUC (Avg.): 49.1 -> 52.3Helped
Add the region layer to ConvNet (ablation)DRML · BP4D, AU 1F1-frame: 40.4 -> 36.4Hurt
Add the region layer to ConvNet (ablation)DRML · DISFA, AU 4F1-frame: 28.9 -> 37.4Helped

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