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Integration effect of artificial intelligence and traditional animation creation technology

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Abstract Despite the advancements in modern computer hardware and software, the creation of digital animation still demands a substantial investment of both manpower and time. This article aimed to explore how artificial intelligence (AI) technology can be combined with traditional animation creation techniques to achieve better integration effects. By combining intelligent character animation generation with hand drawing, a generative adversarial network was used to achieve high-quality animation generation. The generator generated realistic animations, and the discriminator measured the authenticity of the animations by comparing the differences between the generator-generated animations and the real animations, which was used for automated character animation generation. This can greatly reduce the cost and time of digital animation creation, improve the quality of digital animation, and provide more innovation for the application of traditional animation technology. The average number of audience attracted by characters through blended creation was 122.2% more than that of characters through traditional animation creation and 32.6% more than that of characters through AI creation. This not only helps animation producers complete animation production more quickly, but also enhances the creativity and artistic value of animation.
Title: Integration effect of artificial intelligence and traditional animation creation technology
Description:
Abstract Despite the advancements in modern computer hardware and software, the creation of digital animation still demands a substantial investment of both manpower and time.
This article aimed to explore how artificial intelligence (AI) technology can be combined with traditional animation creation techniques to achieve better integration effects.
By combining intelligent character animation generation with hand drawing, a generative adversarial network was used to achieve high-quality animation generation.
The generator generated realistic animations, and the discriminator measured the authenticity of the animations by comparing the differences between the generator-generated animations and the real animations, which was used for automated character animation generation.
This can greatly reduce the cost and time of digital animation creation, improve the quality of digital animation, and provide more innovation for the application of traditional animation technology.
The average number of audience attracted by characters through blended creation was 122.
2% more than that of characters through traditional animation creation and 32.
6% more than that of characters through AI creation.
This not only helps animation producers complete animation production more quickly, but also enhances the creativity and artistic value of animation.

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