Shape Preserving Facial Landmarks with Graph Attention Networks
SPIGA estimates human face landmarks while preserving shape by combining a CNN with Graph Attention Networks (GATs). It uses a multi-task CNN backbone for features and then employs cascaded GAT regressors to iteratively refine landmark positions. This attention mechanism allows the model to weigh landmark information based on reliability, leading to high accuracy even with challenging appearances.