Single Image 3D without a Single 3D Image

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Multi-view Supervision for Single-View Reconstruction via Differentiable Ray Consistency (2017, background): “rect [8], multi-view [11, 15] or even no supervision [10] predict detailed 2.”
Marr Revisited: 2D-3D Alignment via Surface Normal Prediction (2016, background): “surface normal and depth map) by reasoning about mid-level scene properties, such as discriminative 3D primitives [10], convex and concave edges [11], and style elements harvested by unsupervised learning [12].”
Unsupervised Learning of Depth and Ego-Motion from Video (2017, background): “[11] further show that it is even possible to learn 3D inference without 3D labels (or registered 2D views) by utilizing scene regularity.”
Generative Image Modeling Using Style and Structure Adversarial Networks (2016, background): “Finally, the idea of factorizing image into two separate phenomena has been well studied in [46,47,48,49], which motivates us to decompose the generative process to structure and style.”