RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network

Understand

This work introduces RevSilo, the first reversible bidirectional multi-scale feature fusion module.

• Like other reversible methods, RevSilo eliminates the need to store hidden activations by recomputing them.
• However, existing reversible methods do not apply to multi-scale feature fusion and are, therefore, not applicable to a large class of networks.
• Bidirectional multi-scale feature fusion promotes local and global coherence and has become a de facto design principle for networks targeting spatially sensitive tasks, e.g., HRNet (Sun et al., 2019a) and EfficientDet (Tan et al., 2020).