How iQIYI’s AI Coloring Engine Supercharges Animation Production

China’s comic and animation market is booming, but production costs remain high because coloring is a labor‑intensive, repetitive process that requires many artists to collaborate across stages.

Traditional tools focus on static comics and cannot ensure the style consistency and continuity needed for animated sequences, leading to inefficiencies.

iQIYI introduced an AI coloring engine that leverages deep‑learning techniques, specifically a self‑developed GAN model enhanced with attention mechanisms and semantic reference information. The model combines multiple loss functions for pixel‑level precision, and incorporates dedicated color‑reference and style‑reference modules to enrich color richness and maintain uniform styling across frames.

The engine offers two coloring modes: a proprietary high‑quality style and customizable styles specified by animation studios (e.g., realistic, line‑art, cute). It also provides a layered coloring workflow, allowing professional artists to fine‑tune results and integrate the system directly into industrial production pipelines, while simultaneously building line‑art and style databases.

Key technical components include:

Attention‑based GAN architecture for understanding line drawings.

Semantic reference module ensuring accurate coloring of clothing and accessories.

Color and style reference modules that boost color diversity and style uniformity.

Lighting‑layer sub‑module that can be extended to other domains.

Compared with conventional coloring methods, iQIYI’s engine can color a line‑art image in about 0.7 seconds, delivering several‑fold efficiency gains and an estimated 30% reduction in manual labor for the coloring stage.

Additional benefits highlighted are:

Consistent character styling across animation frames.

Uniform clothing and accessory coloring through semantic guidance.

More vivid and detailed characters thanks to refined network structures and loss functions.