Emotion challenge: building a new photoreal facial performance pipeline for games

Proceedings of the ACM SIGGRAPH Digital Production Symposium(2017)

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摘要
In recent years the expected standard for facial animation and character performance in AAA video games has dramatically increased. The use of photogrammetric capture techniques for actor-likeness acquisition, coupled with video-based facial capture and solving methods, has improved quality across the industry. However, due to variability across project pipelines, increased per-project scope for performance capture, and a reliance on external vendors, it is often challenging to maintain visual consistency from project to project, and even from character to character within a single project. Given these factors, we identified the need for a unified, robust, and scalable pipeline for actor likeness acquisition, character art, performance capture, and character animation.
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