Labeling Panoramas with Spherical Hourglass Networks

• DOI: 10.48550/arxiv.1809.02123
• Publication Date: 2018-01-01
• Authors: Esteves, Carlos; Daniilidis, Kostas; Makadia, Ameesh
• Keywords: FOS: Computer and information sciences; Computer Vision and Pattern Recognition (cs.CV); Computer Science - Computer Vision and Pattern Recognition; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

With the recent proliferation of consumer-grade 360�� 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.<br/>Accepted to the 360{\deg} Perception and Interaction Workshop at ECCV 2018<br/>