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RCOD

Image-to-Image
image-super-resolution
real-world-sr
diffusion
one-step-diffusion
aaai-2026
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metadata 
license: mit
pipeline_tag: image-to-image
tags:
  - image-super-resolution
  - real-world-sr
  - diffusion
  - one-step-diffusion
  - aaai-2026

Realism Control One-step Diffusion for Real-World Image Super-Resolution (RCOD)

Official pretrained model checkpoints for RCOD (AAAI 2026).

Checkpoints Included

File Base Architecture Description
rcod_o.pkl OSEDiff (SD 2.1) Unified RCOD-O denoiser with LDG (Fidelity / Neutral / Realism)
rcod_s.pkl S3Diff (SD-Turbo) Unified RCOD-S denoiser with LDG (Fidelity / Neutral / Realism)
rcod_s_mem.pkl MLP Metric Estimation Module (MEM) for adaptive realism selection

External Dependencies

For training and external components, please download the respective third-party models from their original authors:

  • DAPE (DAPE.pth): Domain-Adaptive Prior Extractor from OSEDiff / DAPE.
  • RAM (ram_swin_large_14m.pth): Recognize Anything Model from xinyu1205/recognize-anything.
  • de_net (de_net.pth): Degradation Estimator from S3Diff (included in RCOD_S/assets/mm-realsr/).

Quick Download 

# Using huggingface-cli
pip install huggingface_hub
huggingface-cli download MMQDD/RCOD --local-dir weights/