论文标题
立体声非结构化放大倍率：视图合成的多个同构图像
Stereo Unstructured Magnification: Multiple Homography Image for View Synthesis
论文作者
论文摘要
本文研究了一对图像的一定量旋转的视图问题，我们称之为立体声的非结构化放大倍率。尽管多平面图像表示非常适合与深度不变的视图合成，但如何将其推广到非结构化视图仍然是一个重大挑战。这主要是由于相机正面平行表示引起的深度依赖性。在这里，我们提出了一种新型的多谱图像（MHI）表示，包括一组具有固定正常和距离的场景平面。开发了一个两阶段的网络供新型视图合成。阶段1是一个MHI重建模块，可预测MHIS和复合材料沿正常方向分层的多正常图像。第2阶段是一个普通的混合模块，可以找到混合重量。我们还得出了基于角度的成本，以通过利用人均几何形状来指导多正常图像的混合。与最先进的方法相比，我们的方法在定性和定量上取得了卓越的性能，尤其是对于摄像机进行旋转的情况。
This paper studies the problem of view synthesis with certain amount of rotations from a pair of images, what we called stereo unstructured magnification. While the multi-plane image representation is well suited for view synthesis with depth invariant, how to generalize it to unstructured views remains a significant challenge. This is primarily due to the depth-dependency caused by camera frontal parallel representation. Here we propose a novel multiple homography image (MHI) representation, comprising of a set of scene planes with fixed normals and distances. A two-stage network is developed for novel view synthesis. Stage-1 is an MHI reconstruction module that predicts the MHIs and composites layered multi-normal images along the normal direction. Stage-2 is a normal-blending module to find blending weights. We also derive an angle-based cost to guide the blending of multi-normal images by exploiting per-normal geometry. Compared with the state-of-the-art methods, our method achieves superior performance for view synthesis qualitatively and quantitatively, especially for cases when the cameras undergo rotations.
