Houji Wen

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model

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-Training Quantization (PTQ) is a widely used technique for model compres