Optimizing 360 photos at scale

What this post added

This post details the reengineering of Facebook's photo infrastructure to support "tiled" storage and serving of 360 photo content. It describes converting 360 photos to cube maps, storing them at multiple resolutions, and splitting each resolution into 512x512 tiles. The system dynamically calculates and serves necessary tiles for rendering based on the user's view, falling back to lower resolutions when high-res content is unavailable. It also introduces the use of deep neural networks (modified AlexNet) for automatically correcting the tilt and roll of 360 photos, trained on equirectangular projections and cast as a regression problem to estimate rotation parameters, achieving an average accuracy within 0.1 degrees.