AtG-ContextNet: a temporal attention and hybrid gating architecture for facial blendshape coefficient regression

Driving facial expressions is critical for digital animation, yet resource-constrained systems still rely heavily on linear blendshape models. Existing methods struggle with feature redundancy in high-dimensional landmark prediction and numerical instability in extreme expression regions. To address these, we propose Attention-Gate ContextNet (AtG-ContextNet),a regression framework that integrates a temporal attention mechanism with a Hybrid Gating System. AtG-ContextNet utilizes a region-aware