论文标题
使用双域特征流和多视图幻觉生成纹理
Texture Generation Using Dual-Domain Feature Flow with Multi-View Hallucinations
论文作者
论文摘要
我们提出了一个双域生成模型，以从单个图像中估算一个纹理图，以使3D人类模型着色。当估计纹理图时，单个图像不足，因为它仅显示3D对象的一个方面。为了提供足够的信息来估计完整的纹理图，提出的模型同时在图像域中生成多视图幻觉，并在纹理域中生成估计的纹理图。在生成过程中，每个域发生器通过基于流的本地注意机制将特征交换到另一个特征。通过这种方式，提出的模型可以估算利用丰富的多视图图像特征的纹理图，从而从中生成多视幻觉。结果，估计的纹理图在整个区域中包含一致的颜色和图案。实验显示了我们模型对直接渲染纹理图的优越性，该图适用于3D动画渲染。此外，我们的模型还提高了姿势和观点转移任务的图像域的整体发电质量。
We propose a dual-domain generative model to estimate a texture map from a single image for colorizing a 3D human model. When estimating a texture map, a single image is insufficient as it reveals only one facet of a 3D object. To provide sufficient information for estimating a complete texture map, the proposed model simultaneously generates multi-view hallucinations in the image domain and an estimated texture map in the texture domain. During the generating process, each domain generator exchanges features to the other by a flow-based local attention mechanism. In this manner, the proposed model can estimate a texture map utilizing abundant multi-view image features from which multiview hallucinations are generated. As a result, the estimated texture map contains consistent colors and patterns over the entire region. Experiments show the superiority of our model for estimating a directly render-able texture map, which is applicable to 3D animation rendering. Furthermore, our model also improves an overall generation quality in the image domain for pose and viewpoint transfer tasks.
