发表机构
Australian National University; University of Oxford（澳大利亚国立大学; 牛津大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
AnimalLift提出从单张图像重建结构化、可动画化的3D动物资产，通过统一规范空间和UV对齐毛发贴图实现几何、纹理与毛发的联合预测，支持动画、编辑与模拟。
AI 中文摘要
从单张图像重建完全可动画化的3D动物仍然具有挑战性，因为可用于动画制作的资产不仅需要合理的几何形状，还需要统一的拓扑结构、可编辑的外观以及与变形和模拟兼容的毛发表示。现有的图像到3D方法通常依赖隐式或松散结构的表示，这些表示难以进行骨骼绑定或编辑，而参数化动物模型支持动画但无法捕捉详细的纹理和毛发外观。我们提出了AnimalLift，一个从单张图像重建具有显式毛发的结构化、动画兼容3D动物资产的框架。我们的方法将输入图像提升到一个共享的规范空间，该空间在数据集上具有一致的拓扑结构和UV参数化，从而在统一的前馈架构中实现规范几何、纹理和毛发的联合预测。我们表示的一个关键组成部分是UV对齐的毛发贴图，它在表面对齐的规范域中编码发丝几何，使得显式毛发重建与网格变形和毛发模拟兼容。为了训练模型，我们引入了一个程序化数据生成管道，该管道在不同动物物种和外观上提供具有对齐几何、纹理和毛发的大规模监督。在合成和真实世界数据集上的实验证明了强大的重建质量和跨动物类别的泛化能力。除了重建之外，我们的结构化表示直接支持下游应用，包括动画、姿态迁移、毛发编辑和模拟兼容渲染。
英文摘要
Reconstructing a fully animatable 3D animal from a single image remains challenging because animation-ready assets require not only plausible geometry, but also a unified topology, editable appearance, and fur representations compatible with deformation and simulation. Existing image-to-3D approaches often rely on implicit or loosely structured representations that are difficult to rig or edit, while parametric animal models support animation but cannot capture detailed texture and fur appearance. We present AnimalLift, a framework for reconstructing structured, animation-compatible 3D animal assets with explicit fur from a single image. Our method lifts an input image into a shared canonical space with a consistent topology and UV parameterization across the dataset, enabling joint prediction of canonical geometry, texture, and fur in a unified feed-forward architecture. A key component of our representation is a UV-aligned fur map that encodes strand geometry in a surface-aligned canonical domain, allowing explicit fur reconstruction compatible with mesh deformation and fur simulation. To train the model, we introduce a procedural data generation pipeline that provides large-scale supervision with aligned geometry, texture, and fur across diverse animal species and appearances. Experiments on synthetic and real-world datasets demonstrate strong reconstruction quality and generalization across animal categories. Beyond reconstruction, our structured representation directly supports downstream applications including animation, pose transfer, fur editing, and simulation-compatible rendering.
Journal refSiggraph Asia 2026
