Hello,thanks for this fantastic work.
I found something that I would like to discuss with you.
I found that this framework can't work when I test the dataset of one human in the indoor room with less translation,which means the human is always in the center of the image, just like for those video we take the video setting the camera rotating the human.
I think that's because for these kind of data even though we use masks to ignore the human features but we still have strong human points cloud.
And these points cloud would tends to be optimized first when we using Gaussian splatting which leads to small and weak gradients flow to the smpl points.
Do you have any ideas for this problem?
Hello,thanks for this fantastic work.
I found something that I would like to discuss with you.
I found that this framework can't work when I test the dataset of one human in the indoor room with less translation,which means the human is always in the center of the image, just like for those video we take the video setting the camera rotating the human.
I think that's because for these kind of data even though we use masks to ignore the human features but we still have strong human points cloud.
And these points cloud would tends to be optimized first when we using Gaussian splatting which leads to small and weak gradients flow to the smpl points.
Do you have any ideas for this problem?