SLIM: Diffusion-Powered Image Compression for Machines
Published:Dec 20, 2025 03:48
•1 min read
•ArXiv
Analysis
This research explores a novel approach to image compression using diffusion models, potentially enabling more efficient data storage and transmission for machine learning applications. The use of semantic information to inform the compression process is a promising direction for achieving higher compression ratios.
Key Takeaways
- •SLIM utilizes diffusion models for image compression.
- •The compression method is designed for machine learning applications.
- •Semantic information is leveraged to improve compression efficiency.
Reference
“The paper focuses on Semantic-based Low-bitrate Image compression for Machines.”