Few-step Generative Models as Lossy Compression
Researchers have developed a novel method to adapt few-step generative models for lossy compression tasks. By leveraging frameworks like reverse channel coding (RCC), models such as Rectified Flow, Consistency Trajectory Models (CTM), and MeanFlow can be repurposed as codecs. This approach allows for faster encoding and decoding times, particularly in low-bit-rate scenarios, and enhances realism without requiring model retraining. AI
IMPACT Enables faster and more realistic data compression using generative AI models.