论文标题
来自单个快照图像的Omni方向图像生成
Omni-Directional Image Generation from Single Snapshot Image
论文作者
论文摘要
Omni方向图像（ODI）是具有覆盖相机周围整个球体的视野的图像。 ODI已开始在虚拟现实（VR），机器人技术和社交网络服务等广泛领域中使用。尽管使用ODI的内容增加了，但与广泛的快照图像相比，可用的图像和视频仍然有限。不仅需要VR内容，而且还需要大量ODI，还需要为ODI培训深度学习模型。为了这些目的，本文提出了一项新的计算机视觉任务，以从单个快照图像中产生ODI。为了解决这个问题，将有条件的生成对抗网络与集体条件的卷积层结合使用。有了这项新颖的任务，即使使用智能手机相机，VR图像和视频也将很容易创建。
An omni-directional image (ODI) is the image that has a field of view covering the entire sphere around the camera. The ODIs have begun to be used in a wide range of fields such as virtual reality (VR), robotics, and social network services. Although the contents using ODI have increased, the available images and videos are still limited, compared with widespread snapshot images. A large number of ODIs are desired not only for the VR contents, but also for training deep learning models for ODI. For these purposes, a novel computer vision task to generate ODI from a single snapshot image is proposed in this paper. To tackle this problem, the conditional generative adversarial network was applied in combination with class-conditioned convolution layers. With this novel task, VR images and videos will be easily created even with a smartphone camera.
