We introduce context-aware translation, a novel method that combines the benefits of inpainting and image-to-image translation, respecting simultaneously the original input and contextual relevance -- where existing methods fall short. By doing so, our method opens new avenues for the controllable use of AI within artistic creation, from animation to digital art. As an use case, we apply our method to redraw any hand-drawn animated character eyes based on any design specifications - eyes serve as a focal point that captures viewer attention and conveys a range of emotions, however, the labor-intensive nature of traditional animation often leads to compromises in the complexity and consistency of eye design. Furthermore, we remove the need for production data for training and introduce a new character recognition method that surpasses existing work by not requiring fine-tuning to specific productions. This proposed use case could help maintain consistency throughout production and unlock bolder and more detailed design choices without the production cost drawbacks. A user study shows context-aware translation is preferred over existing work 95.16% of the time.

介绍了一种上下文感知翻译方法，将修补和图像转换的优点相结合，同时尊重原始输入和上下文相关性，为艺术创作中AI的可控使用开辟了新途径。作为一个应用案例，我们将该方法应用于根据任何设计规范重绘任何手绘动画角色的眼睛 - 眼睛作为吸引观众注意力和传递一系列情绪的焦点，然而，传统动画的劳动密集型特性常常导致眼睛设计的复杂性和一致性上的妥协。此外，我们消除了对训练生产数据的需求，并引入了一种新的字符识别方法，超越了现有工作，不需要针对特定制作进行微调。该应用案例有助于在制作过程中保持一致性，并在无需生产成本的情况下释放出更大胆和更详细的设计选择。用户研究表明，上下文感知翻译比现有方法更受青睐，达到95.16%的时间。

Re:Draw--上下文感知翻译作为艺术创作的可控方法