Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition
Leading entries on the multi-task track of the 11th ABAW challenge rely on heavy ensembling, yet which member is worth adding to an already strong ensemble is rarely made explicit. We study this question for joint valence-arousal estimation, 8-way expression recognition, and 12-way action-unit detection from a single unconstrained face, under partial, long-tailed labels and a rule that forbids pretraining on Aff-Wild2. Building on a shared affect-latent that marginalizes the missing labels across two affect-supervised backbones, we propose a strength-parity rule: an added member lowers the ensemble error only when it is both decorrelated from the current members and a near-peer of them in...
| Authors | Tung Hung Bui, Hong Hai Nguyen, Van Thong Huynh |
|---|---|
| Primary category | cs.CV |
| Published | 12 July 2026 |
| Last updated at source | 21 July 2026 |
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