صورة الغلاف

Artificial Intelligence-Driven Physical Simulation and Animation Generation in Computer Graphics

محفوظ في:
الحاوية / القاعدة:International Journal of Advanced Computer Science and Applications vol. 16, no. 5 (2025)
المؤلف الرئيسي: PDF
منشور في:
Science and Information (SAI) Organization Limited
الموضوعات:
Smoothness
Animation
Artificial intelligence
Physical simulation
Computer graphics
Generative adversarial networks
Deep learning
Computer science
Realism
Neural networks
Quantitative analysis
الوصول للمادة أونلاين:Citation/Abstract
Full Text - PDF
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مستخلص:This study explores an expression synthesis algorithm anchored in Generative Adversarial Networks (GAN) with attention mechanisms, achieving enhanced authenticity in facial expression generation. Evaluated on the MUG and Oulu-CASIA datasets, our method synthesizes six expressions with superior clarity (96.63±0.26 confidence for neutral expressions) and smoothness (SSIM >0.92 for video frames), outperforming StarGAN and ExprGAN in detail preservation and temporal stability. The proposed model demonstrates significant advantages in realism and identity retention, validated through quantitative metrics and comparative experiments.
تدمد:2158-107X
2156-5570
DOI:10.14569/IJACSA.2025.0160568
المصدر:Advanced Technologies & Aerospace Database