Taskonomy: Disentangling Task Transfer Learning
The authors propose a computational method to map visual tasks into a structure called a taxonomic map by finding dependencies between them in latent space. This allows for learning how to transfer knowledge efficiently between different tasks, reducing the data needed for training and creating more predictable perception models.