AI RESEARCH
Improving Generative Adversarial Network Generalization for Facial Expression Synthesis
arXiv CS.LG
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ArXi:2603.15648v1 Announce Type: cross Facial expression synthesis aims to generate realistic facial expressions while preserving identity. Existing conditional generative adversarial networks (GANs) achieve excellent image-to-image translation results, but their performance often degrades when test images differ from the