A novel method for composite facial expressions generation based on multimodal reinforcement learning

Key Points

• The novel method generates composite facial expressions effectively, enhancing realism in digital interactions.
• Accuracy reached over 85% in simulating various facial expressions based on multimodal inputs.
• Assessment utilized multimodal reinforcement learning techniques to improve expression generation and representation.
• These findings may enable more realistic avatars and assistive technologies in virtual reality environments.