[论文解读] SMAL-pets: SMAL Based Avatars of Pets from Single Image

Piotr Borycki, Joanna Waczyńska+3 more|arXiv (Cornell University)|Mar 17, 2026

3D Shape Modeling and Analysis被引用 0

一句话总结

论文提出 SMAL-pets，一种从单张图像创建基于 SMAL 的宠物形象的方法。

ABSTRACT

Creating high-fidelity, animatable 3D dog avatars remains a formidable challenge in computer vision. Unlike human digital doubles, animal reconstruction faces a critical shortage of large-scale, annotated datasets for specialized applications. Furthermore, the immense morphological diversity across species, breeds, and crosses, which varies significantly in size, proportions, and features, complicates the generalization of existing models. Current reconstruction methods often struggle to capture realistic fur textures. Additionally, ensuring these avatars are fully editable and capable of performing complex, naturalistic movements typically necessitates labor-intensive manual mesh manipulation and expert rigging. This paper introduces SMAL-pets, a comprehensive framework that generates high-quality, editable animal avatars from a single input image. Our approach bridges the gap between reconstruction and generative modeling by leveraging a hybrid architecture. Our method integrates 3D Gaussian Splatting with the SMAL parametric model to provide a representation that is both visually high-fidelity and anatomically grounded. We introduce a multimodal editing suite that enables users to refine the avatar's appearance and execute complex animations through direct textual prompts. By allowing users to control both the aesthetic and behavioral aspects of the model via natural language, SMAL-pets provides a flexible, robust tool for animation and virtual reality.

研究动机与目标

• 从单张图像推动创建基于 SMAL 的宠物头像。
• 利用 SMAL 表示进行宠物建模。
• 实现真实的重建与潜在的宠物头像下游应用。

提出的方法

• 提出基于 SMAL 框架的 SMAL-pets。
• 进行单图推断以生成宠物头像。
• 利用参数估计或优化过程将 SMAL 参数拟合到输入图像。
• 生成适合渲染和动画的三维友好表示。

实验结果

研究问题

• RQ1 是否可以推断出基于 SMAL 的表示，以从单张图像产出宠物头像？
• RQ2 从一张照片可以多大程度上准确重建宠物的形状与姿态？
• RQ3 SMAL-pets 在不同宠物物种上的泛化能力如何？

主要发现

• 在可获取的文本片段中未提供定量结果。
• 该方法暗示了从单张图像得到基于 SMAL 的宠物头像的定性可信性。
• 提供的文本片段不包含实验指标或数据集细节。