NiFangBaAGe / CoordFill

[AAAI 2023] CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying
BSD 3-Clause "New" or "Revised" License
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reproduction problem #6

Closed zhao2000hhh closed 1 year ago

zhao2000hhh commented 1 year ago

When I retrained with your training code and configuration, I couldn't produce a model as good as yours。 Specifically, I tried on the celeba-HQ dataset. mask ftom https://nv-adlr.github.io/publication/partialconv-inpainting train on 20-30% subset test on the whole mask set my model: psnr=28.5719, val: ssim=0.8786, val: lpips=0.0945 your model: PSNR = 29.581334 SSIM= 0.893 LPIPS=0.08094 Do you have any special training techniques? Looking forward to your reply.

NiFangBaAGe commented 1 year ago

Thanks for your interest in our work. The masks for experiments are generated from https://nv-adlr.github.io/publication/partialconv-inpainting. We dilate or erode them to ensure the mask ratio is not more than 25% (following HiFill).

zhao2000hhh commented 1 year ago

Is the testing also conducted on the 25%mask?

NiFangBaAGe commented 1 year ago

Yes, all the training and testing masks follow this setting.

zhao2000hhh commented 1 year ago

thank you reply. By the way, could you share me the 25% mask?

zhao2000hhh commented 1 year ago

looking forward to your reply. sos

NiFangBaAGe commented 1 year ago

The mask is available here. Hope it can help you.

zhao2000hhh commented 1 year ago

good luck!