CG Animation Creator: Auto-rendering of Motion Stick Figure Based on Conditional Adversarial Learning

Jie Lin, Jian Cui, Guangming Shi, Danhua Liu

Abstract: As an important part of animation production, the existing method for drawing and rendering the CG animated characters according to motion information mostly relays on expensive manual processing. By adopting the conditional adversarial learning, an automatic animation rendering system for geometry structure attribute is proposed, using a deep convolution generative adversarial network called “pix2pixHD”. A training database containing a variety of motion stick figure is established for different virtual characters to achieve an end-to-end training system to verify this idea. The trained generator is the desired CG animation creator which shows great performance on visual quality and time efficiency proved by the experimental results.