Closed Pixie8888 closed 6 months ago
The input image range should be 0 to 1 (float). Because of the artifacts in the bottom of the scene, I think this could be a problem with the input data format. What's the dataset you're using? And are you trying to train on the dataset or evaluate a pre-trained checkpoint on new data?
I am using scannet. The input image is normalized to 0~1 (float). I uses the provided intrinsic and extrinsic by scannet. The intrinsic is normalized by image width and height. I am training a new model on it.
Some more things to try:
I might be able to come up with some more ideas if there are more details you can provide. I haven't seen the artifacts/black dots while training on RE10k and ACID though, so I'm not sure what causes those. Good luck!
Dear author, I found the main reason is that I mistakenly set the opacity to be always 1 and downsampled the src image to be smaller than target image that causes these artifacts. Thank you very much for your kind help!
Dear author,
I am using pixelsplat on my own datset. But the result is very bad, like this below. I don't know what caused the pattern of lower left and right. Also, why there are so many black dots? I set background color to black, and I checked the image value is within 0~255. Do you have any suggestions for debugging? Thank you very much!