Recently, a research team released a new image super-resolution (SR) technology based on Diffusion Inversion. This technology aims to enhance image resolution and clarity by fully utilizing the prior information of images contained in large pre-trained diffusion models. The study was collaboratively conducted by three scholars from different academic institutions, with the goal of bringing new breakthroughs to the field of image super-resolution.
In this technology, the researchers designed a strategy called "Partial Noise Prediction," which constructs intermediate states of the diffusion model as starting sampling points. This core method relies on a deep noise predictor capable of providing the optimal noise map for the forward diffusion process. After training, this noise predictor can partially initialize the sampling process, generating high-resolution images along the diffusion trajectory.
Compared to existing super-resolution methods, this technology features a more flexible and efficient sampling mechanism that supports any number of sampling steps from one to five. Notably, even when using just one sampling step, the performance of this new method surpasses or is comparable to current state-of-the-art techniques.
The research team also provided detailed usage instructions and training guidance, including the required software and hardware environment, download links for the model, and how to run the program under limited GPU memory conditions. This information will help researchers and developers better utilize the technology for image super-resolution related work.
Additionally, the research team has set up an online demonstration platform, allowing users to intuitively experience this innovative technology, and provided links to synthetic and real datasets for validating research results. The researchers hope that this technology can offer more efficient and clearer solutions for practical applications in image super-resolution.
Project link: https://github.com/zsyOAOA/InvSR?tab=readme-ov-file
Demo: https://huggingface.co/spaces/OAOA/InvSR
Key Points:
🌟 This new technology, based on diffusion inversion, effectively enhances image resolution.
🔍 Utilizes the "Partial Noise Prediction" strategy, flexibly supporting different sampling steps.
💻 Provides comprehensive usage guidelines and an online demo for user convenience.
