arXiv 论文：为多部件动漫 3D 模型生成 ARKit/MediaPipe 表情 Blendshape
Blendshape Generation for Models with Disconnected Parts: Adding ARKit/MediaPipe Blendshapes to Anime-Style Character Models
做 VRM/VTuber 模型的朋友可以看看，这篇讲怎么给多部件的动漫脸自动生成 ARKit 表情，省去手动 K 帧的活。
一篇 arXiv 论文研究了为多个不相连部件组成的 3D 模型生成表情 blendshape 的问题，案例对象是每张脸最多 11 个部件的商业动漫风格角色模型。方法上，团队训练神经网络在输入网格周围生成形变场，每个部件至少由一个网络独立处理，并通过让网络同时处理锚定部件的几何信息来协调输出位置。论文用两个机制提升精度：让网络预测位移是否为零，以及按大小分组为不同 blendshape 分配专门网络。作者还提出一种增强双侧对称性的方法来改善 blendshape 质量。
Blendshape Generation for Models with Disconnected Parts: Adding ARKit/MediaPipe Blendshapes to Anime-Style Character Models
Blendshape generation for 3D models has been extensively researched, but very few works address generating blendshapes for models with multiple disconnected parts. We present a case study of generating fixed facial expression blendshapes for commercial anime-style 3D character models with up to 11 parts per face. To make sure that our system can handle models in a way that is agnostic to topology, we train neural networks to generate deformation fields around the input meshes. We employ at least one network to independently process each part, and the relative positions of their outputs are coordinated by having each network also process the geometry of an anchor part. We use two mechanisms to improve accuracy: having the networks predict whether the output displacement is zero or not, and classifying blendshapes into different size groups and dedicating a network to each group. We also introduce a method to improve blendshape quality by enhancing bilateral symmetry. Our method is simpler than recent neural-network-based works and solves a real problem of the user community of these models.