AI RESEARCH
Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration
arXiv CS.CV
•
ArXi:2503.21970v3 Announce Type: replace State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length while effectively capturing long-distance dependencies. However, deploying SSMs to edge devices is challenging due to the constraints in memory, computing capacity, and power consumption, underscoring the need for efficient compression strategies.