Artificial Intelligence-Driven Physical Simulation and Animation Generation in Computer Graphics
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| Publicado en: | International Journal of Advanced Computer Science and Applications vol. 16, no. 5 (2025) |
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| Autor principal: | |
| Publicado: |
Science and Information (SAI) Organization Limited
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 024 | 7 | |a 10.14569/IJACSA.2025.0160568 |2 doi | |
| 035 | |a 3222641077 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a PDF | |
| 245 | 1 | |a Artificial Intelligence-Driven Physical Simulation and Animation Generation in Computer Graphics | |
| 260 | |b Science and Information (SAI) Organization Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Smoothness | ||
| 653 | |a Animation | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Physical simulation | ||
| 653 | |a Computer graphics | ||
| 653 | |a Generative adversarial networks | ||
| 653 | |a Deep learning | ||
| 653 | |a Computer science | ||
| 653 | |a Realism | ||
| 653 | |a Neural networks | ||
| 653 | |a Quantitative analysis | ||
| 773 | 0 | |t International Journal of Advanced Computer Science and Applications |g vol. 16, no. 5 (2025) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222641077/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222641077/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |