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Hi CogView team. First off, great work! This method's results are very impressive. I just wanted to post some observations that I've had that might help inform future roadmap.
Generations tend to include watermarks and other artifacts of online images. One common one I see is a white bar at the bottom with black pseudo-text (see examples below)
Add support for non-square inpainting/replacement boundaries.
Hands and arms seem to be deformed, have extra fingers, etc. Suggest adding more data with pictures of hands to help model fix those issues.
Congrats on the paper and keep up the good work!
The text was updated successfully, but these errors were encountered:
Cogview2 appears to have been trained on stock photos and I'm guessing many of the training images had the white bar so I'm not sure how it can be easily avoided. It is a great development and making the model freely available is great.
I have also observed the white bars or other watermarks, we will collect more data and also clean the data in the following works!
The non-square inpainting/replacement boundaries is supported, but I don't know how to input the mask and don't have a enough time to write a UI... I will work on that afterwards.
The reasons might be more complex and I will improve the method in the following works.
Hi CogView team. First off, great work! This method's results are very impressive. I just wanted to post some observations that I've had that might help inform future roadmap.
Generations tend to include watermarks and other artifacts of online images. One common one I see is a white bar at the bottom with black pseudo-text (see examples below)


Add support for non-square inpainting/replacement boundaries.
Hands and arms seem to be deformed, have extra fingers, etc. Suggest adding more data with pictures of hands to help model fix those issues.
Congrats on the paper and keep up the good work!
The text was updated successfully, but these errors were encountered: