A novel post-training quantization scheme, QNCD, that effectively mitigates both intra and inter quantization noise in diffusion models, enabling efficient low-bit inference while preserving high-quality image synthesis.
An accurate post-training quantization framework for diffusion models that reduces quantization errors across generation timesteps and selects optimal calibration images to enable efficient image generation.