  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.
