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How to train a Gaussian model using a background-removed dataset? #2764

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GuoFengYung opened this issue Jan 15, 2024 · 4 comments
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How to train a Gaussian model using a background-removed dataset? #2764

GuoFengYung opened this issue Jan 15, 2024 · 4 comments

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@GuoFengYung
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GuoFengYung commented Jan 15, 2024

Describe
I use the GS model to train the transparency dataset, but the trained background has many clouds.
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Screenshot from 2024-01-15 14-14-17

@brentyi
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brentyi commented Jan 15, 2024

Not my area of expertise, but nerfstudio-project/gsplat#70 seems relevant!

@GuoFengYung
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thank you for your reply!
I will researching it

@KevinXu02
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KevinXu02 commented Jan 16, 2024

A fast but inelegant method is to directly inject white bg colour into GS model, I've test it with LEGO dataset in #2704. And then you can transit the rgb image with white bg to a rgba one. I think the main problem is that when training GS model the bg colour is ramdomly picked, we may need a alpha for the bg and add it into the BP and FP I think? nerfstudio-project/gsplat#70 seems only apply alpha output to gaussians, but I think it will immediately work by adding alpha for the bg and setting it to 0.

@GuoFengYung
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Yes, I currently use a white background to run training

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