WSVD

We present a fully data-driven method to compute depth from diverse monocular video sequences that contain large amounts of non-rigid objects, e.g., people. To learn reconstruction cues for non-rigid scenes, we introduce a new dataset (WSVD) consisting of stereo videos scraped from Youtube. This dataset has a wide variety of scene types, and features many nonrigid objects.

我们提出了一种全数据驱动方法，可从包含大量非刚性物体（例如人体）的多样化单目视频序列中计算深度。为了学习非刚性场景的重建线索，我们引入了一个全新的数据集（WSVD），该数据集由从YouTube爬取得到的立体视频构成。本数据集涵盖了丰富多样的场景类型，且包含大量非刚性物体。