Hello! Congratulations on your excellent work!
I am highly interested in the construction process of your multi-view consistent image editing dataset. To explore this, I recently conducted some experiments using the FLUX.1-Kontext-dev model, where I horizontally concatenated two images as the input.
However, I encountered a couple of issues during my experiments:
(1) Global Alteration during Local Editing: When the target editing area is strictly local, the model tends to rewrite the entire image, causing unintended changes to the background.
(2) Resolution and Sizing Inconsistency: The model seems to automatically resize my original images, which results in a mismatch between the dimensions of the input and the generated output.
I was wondering if you encountered these similar challenges when building your dataset? If so, how did you effectively resolve them?
I would truly appreciate your insights on this. I am eagerly looking forward to your reply, as well as the upcoming release of your code and datasets!
Thank you very much for your time and help.
Hello! Congratulations on your excellent work!
I am highly interested in the construction process of your multi-view consistent image editing dataset. To explore this, I recently conducted some experiments using the FLUX.1-Kontext-dev model, where I horizontally concatenated two images as the input.
However, I encountered a couple of issues during my experiments:
(1) Global Alteration during Local Editing: When the target editing area is strictly local, the model tends to rewrite the entire image, causing unintended changes to the background.
(2) Resolution and Sizing Inconsistency: The model seems to automatically resize my original images, which results in a mismatch between the dimensions of the input and the generated output.
I was wondering if you encountered these similar challenges when building your dataset? If so, how did you effectively resolve them?
I would truly appreciate your insights on this. I am eagerly looking forward to your reply, as well as the upcoming release of your code and datasets!
Thank you very much for your time and help.