metadata

license: apache-2.0

[CVPR2024 Oral] Image Processing GNN: Breaking Rigidity in Super-Resolution

Paper | Project Page |

This is the official repo of our CVPR'24 paper **Image Processing GNN: Breaking Rigidity in Super-Resolution**. In the paper, we propose IPG: a Graph-based SR model that achieves outstanding performance on various SR benchmarks.

News

7/6/2024: We opensourced the code & weights of IPG!

6/19/2024: Our work got the Best Student Runner-up Award of CVPR'24!🎉🎉

6/2/2024: We open-sourced U-DiT, an efficient U-Net-style DiT variant.

Weights & Visual Results

Model	Scale	Urban100	Weights	Visual Results
IPG	2x	34.48	🤗Link	🤗Link
IPG	3x	30.36	🤗Link	🤗Link
IPG	4x	28.13	🤗Link	🤗Link