GM-MoE: Low-Light Enhancement with Gated-Mechanism Mixture-of-Experts

Understand

Low-light enhancement has wide applications in autonomous driving, 3D reconstruction, remote sensing, surveillance, and so on, which can significantly improve information utilization.

• However, most existing methods lack generalization and are limited to specific tasks such as image recovery.
• To address these issues, we propose Gated-Mechanism Mixture-of-Experts (GM-MoE), the first framework to introduce a mixture-of-experts network for low-light image enhancement.
• GM-MoE comprises a dynamic gated weight conditioning network and three sub-expert networks, each specializing in a distinct enhancement task.