论文标题
世界表：将世界包裹在3D纸上以查看单图片的综合
Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image
论文作者
论文摘要
我们提出世界表，这是一种仅使用单个RGB图像作为输入的新型视图合成方法。主要的见解是，只需将平面网状纸缩小到输入图像上，与所学的中间深度一致，捕获足以产生具有较大视图的变化的光真逼真的视图的基础几何形状。为了实现这一目标，我们提出了一个新颖的可区分纹理采样器，该采样器允许从目标角度将包裹的网格表纹理和差异化为图像。我们的方法是无需使用任何3D监督的端到端类别的，端到端的训练，并且需要在测试时进行单个图像。我们还通过堆叠多个世界表格以更好地处理闭塞来探索简单的扩展。在几个数据集上，世界表始终优于单图视图合成的先前最新方法。此外，这个简单的想法在各种高分辨率的内部图像上捕捉了令人惊讶的景观，从而将其转换为可通航的3D弹出窗口。视频结果和代码可从https://worldsheet.github.io获得。
We present Worldsheet, a method for novel view synthesis using just a single RGB image as input. The main insight is that simply shrink-wrapping a planar mesh sheet onto the input image, consistent with the learned intermediate depth, captures underlying geometry sufficient to generate photorealistic unseen views with large viewpoint changes. To operationalize this, we propose a novel differentiable texture sampler that allows our wrapped mesh sheet to be textured and rendered differentiably into an image from a target viewpoint. Our approach is category-agnostic, end-to-end trainable without using any 3D supervision, and requires a single image at test time. We also explore a simple extension by stacking multiple layers of Worldsheets to better handle occlusions. Worldsheet consistently outperforms prior state-of-the-art methods on single-image view synthesis across several datasets. Furthermore, this simple idea captures novel views surprisingly well on a wide range of high-resolution in-the-wild images, converting them into navigable 3D pop-ups. Video results and code are available at https://worldsheet.github.io.
