论文标题
Zoobuilder：使用合成数据的四足动物的2D和3D姿势估计
ZooBuilder: 2D and 3D Pose Estimation for Quadrupeds Using Synthetic Data
论文作者
论文摘要
这项工作介绍了一种新的策略，该策略用于使用Key Frame Animations生成2D和3D姿势估算动物的合成训练数据。为了自动化为野生动植物创建动画的过程，我们使用合成数据训练了几个2D和3D姿势估计模型，并设置了一条称为Zoobuilder的端到端管道。该管道将作为动物在野外的动物视频输入，并为动物骨骼的每个关节生成相应的2D和3D坐标。通过这种方法，我们产生了运动捕获数据，可用于为野生动植物创建动画。
This work introduces a novel strategy for generating synthetic training data for 2D and 3D pose estimation of animals using keyframe animations. With the objective to automate the process of creating animations for wildlife, we train several 2D and 3D pose estimation models with synthetic data, and put in place an end-to-end pipeline called ZooBuilder. The pipeline takes as input a video of an animal in the wild, and generates the corresponding 2D and 3D coordinates for each joint of the animal's skeleton. With this approach, we produce motion capture data that can be used to create animations for wildlife.
