2d-gaussian-splatting
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Unwanted behaviour when using white background once normal loss starts
I'm training on a set of images that have been preprocessed by applying a segmentation mask, i.e. the background is white.
Training works well up until iteration 7000, which is until the normal loss kicks in:
However, after I start applying the normal loss, I get unwanted gaussians, such as seen here:
Which eventually grow to fill the entire background:
Is there any way to fix this behavior with the current implementation?