With the recent proliferation of consumer-grade 360{\deg} cameras, it is worth revisiting visual perception challenges with spherical cameras given the potential benefit of their global field of view. To this end we introduce a spherical convolutional hourglass network (SCHN) for the dense labeling on the sphere. The SCHN is invariant to camera orientation (lifting the usual requirement for `upright' panoramic images), and its design is scalable for larger practical datasets. Initial experiments show promising results on a spherical semantic segmentation task.

翻译：最近消费者级的360(deg)摄像头激增,鉴于其全球视野的潜在好处,值得以球形照相机重新审视视觉认知挑战。 为此,我们引入球形革命沙子网络(SCHN)用于球体上的密集标签。 SCHN对摄像定向(提高对“直截了当”全景图像的通常要求 ), 其设计可以用于更大的实用数据集。 初步实验显示球形语义分割任务有希望的结果 。