An Energy-Guided Distribution Calibration Method for Open-Set Few-Shot Face Recognition
Open-set few-shot face recognition (OSFSFR) requires both strong generalization from scarce samples and reliable rejection of unknowns. Existing methods discard base-class knowledge after pre-training, while pseudo-labeling suffers from noisy labels and base–novel distribution gaps. We propose the BEDCM, a unified fram...