What is multi-task learning in Computer Vision architectures?

Multi-task learning trains a single model to perform multiple related vision tasks simultaneously.

Instead of training separate models, multi-task learning shares a common backbone and uses task-specific heads. Shared representations improve generalization by learning complementary features. However, balancing task losses is critical to avoid dominance of one task over others.