AI RESEARCH
CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model
arXiv CS.CV
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ArXi:2605.16901v1 Announce Type: new Segment Anything Models (SAMs) are extensively used in computer vision for universal image segmentation, but deploying them on resource-constrained devices is challenging due to their high computational and memory demands. Post-