Learning Single-View 3D Reconstruction with Limited Pose Supervision

A unified framework is presented that can combine both types of supervision: a small amount of camera pose annotations are used to enforce pose-invariance and view-point consistency, and unlabeled images combined with an adversarial loss are use to enforce the realism of rendered, generated models.