  Creating and animating 3D biped cartoon characters is crucial and valuable in
various applications. Compared with geometry, the diverse texture design plays
an important role in making 3D biped cartoon characters vivid and charming.
Therefore, we focus on automatic texture design for cartoon characters based on
input instructions. This is challenging for domain-specific requirements and a
lack of high-quality data. To address this challenge, we propose Make-It-Vivid,
the first attempt to enable high-quality texture generation from text in UV
space. We prepare a detailed text-texture paired data for 3D characters by
using vision-question-answering agents. Then we customize a pretrained
text-to-image model to generate texture map with template structure while
preserving the natural 2D image knowledge. Furthermore, to enhance fine-grained
details, we propose a novel adversarial learning scheme to shorten the domain
gap between original dataset and realistic texture domain. Extensive
experiments show that our approach outperforms current texture generation
methods, resulting in efficient character texturing and faithful generation
with prompts. Besides, we showcase various applications such as out of domain
generation and texture stylization. We also provide an efficient generation
system for automatic text-guided textured character generation and animation.
