shallowdream204/DreamClear
DreamClear is a diffusion-transformer-based image restoration model for removing noise, deblurring, and super-resolution on real-world images.
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This repository provides the official implementation of DreamClear, a high-capacity image restoration method using diffusion transformers. It addresses real-world degradation scenarios including blur, noise, and low resolution, while introducing a privacy-safe approach to dataset curation for training. The model is published at NeurIPS 2024 and weights are available on HuggingFace.
Frequently asked
- What is shallowdream204/DreamClear?
- DreamClear is a diffusion-transformer-based image restoration model for removing noise, deblurring, and super-resolution on real-world images.
- Is DreamClear open source?
- Yes — shallowdream204/DreamClear is open source, released under the Apache-2.0 license.
- What language is DreamClear written in?
- shallowdream204/DreamClear is primarily written in Python.
- How popular is DreamClear?
- shallowdream204/DreamClear has 1.2k stars on GitHub.
- Where can I find DreamClear?
- shallowdream204/DreamClear is on GitHub at https://github.com/shallowdream204/DreamClear.