Artist-Guided Semiautomatic Animation Colorization
This addresses the need for cost reduction and manageable workloads in the animation industry, particularly for studios and outsourced artists, though it is incremental as it builds on existing adversarial methods.
The paper tackles the problem of automating line art colorization in animation while preserving artistic vision, achieving a method that reduces workload by incorporating artist hints and temporal consistency into an adversarial framework.
There is a delicate balance between automating repetitive work in creative domains while staying true to an artist's vision. The animation industry regularly outsources large animation workloads to foreign countries where labor is inexpensive and long hours are common. Automating part of this process can be incredibly useful for reducing costs and creating manageable workloads for major animation studios and outsourced artists. We present a method for automating line art colorization by keeping artists in the loop to successfully reduce this workload while staying true to an artist's vision. By incorporating color hints and temporal information to an adversarial image-to-image framework, we show that it is possible to meet the balance between automation and authenticity through artist's input to generate colored frames with temporal consistency.