We build a heatmap-based landmark detection model to locate important landmarks on 2D RGB garment images. The main goal is to detect edges, corners and suitable interior region of the garments. This let us re-create 3D garments in modern 3D editing software by incorporate landmark detection model and texture unwrapping. We use a U-net architecture with ResNet backbone to build the model. With an appropriate loss function, we are able to train a moderately robust model.

翻译：我们建立了一个基于热地图的里程碑探测模型,以定位2D RGB 服装图像的重要里程碑。 主要目标是探测服装的边缘、 角和合适的内部区域。 这让我们在现代 3D 编辑软件中重新创建 3D 服装, 包括里程碑探测模型和无包装的纹理。 我们使用带有 ResNet 主干线的 U- net 结构来构建模型。 有了适当的损失功能, 我们就可以训练一个适度强健的模型 。