Two-step decoding is a technique used in diffusion-based image compression, enabled by a lightweight consistency estimator. It accelerates the image reconstruction process by preserving the semantic trajectory of diffusion sampling, leading to significant speed-ups and efficient, high-fidelity results.
Two-step decoding is a technique that makes advanced AI image generation and compression much faster. Instead of many complex steps, it reconstructs images in just two quick steps, significantly speeding up the process while keeping the image quality high.
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