AI RESEARCH

Hardware-Aware Neural Feature Extraction for Resource-Constrained Devices

arXiv CS.LG

ArXi:2605.04282v1 Announce Type: new Visual SLAM is a core component of spatial computing systems, yet deploying learned local feature extractors on microcontroller-class hardware remains challenging due to memory, bandwidth, and quantization constraints. While modern neural descriptors provide strong robustness, their practical adoption is often hindered by system-level bottlenecks that are not captured by FLOP-based efficiency metrics. In this work, we