Thanks for open-sourcing this great work! I would like to bring this edge case to your attention:
RALI gives a higher score for a noisy image than for a clean image, when the noise comes from an image editing model.
For example, this clean image receive a score of 3.89.
However, this noisy image after 5 steps by Nano Banana Pro receives a higher RALI score of 3.93, despite obvious visual artifacts.
Traditional NR-IQA metrics also fail in this case. Hope to see future improvements of the Q-Insight model family! You can find a dataset of images corrupted by Nano Banana Pro here.
Thanks for open-sourcing this great work! I would like to bring this edge case to your attention:
RALI gives a higher score for a noisy image than for a clean image, when the noise comes from an image editing model.
For example, this clean image receive a score of 3.89.
However, this noisy image after 5 steps by Nano Banana Pro receives a higher RALI score of 3.93, despite obvious visual artifacts.
Traditional NR-IQA metrics also fail in this case. Hope to see future improvements of the Q-Insight model family! You can find a dataset of images corrupted by Nano Banana Pro here.