Closed Sylvia6 closed 2 years ago
Can it be that these are spots that are not seen during training? So the color is uninitialized?
@darglein But it appears during the training time. I use the dense point cloud map collected from lidar. So some of the views have relatively sparse points, which means there might be more holes in a picture and might be filled with environment map sample texture. I wonder what causes the above abnormal phenomena.
@darglein But it appears during the training time. I use the dense point cloud map collected from lidar. So some of the views have relatively sparse points, which means there might be more holes in a picture and might be filled with environment map sample texture. I wonder what causes the above abnormal phenomena.
您好,我也尝试在自己的数据集上用ADOP进行训练,但有问题出来,可以加下您微信,跟您交流一下吗?
@darglein But it appears during the training time. I use the dense point cloud map collected from lidar. So some of the views have relatively sparse points, which means there might be more holes in a picture and might be filled with environment map sample texture. I wonder what causes the above abnormal phenomena.
Sorry for troubing you. I also have some problem when test the algorithm on lidar point cloud. I build the lidar point cloud densly. However, when I train the algorithm. There are a lot of black holes on the viewer GUI. I debug the point_cloud_initial, it still densely enough. I really don't know why
Hi,I have some doubt of my train result on other dataset. It looks like below:( left picture is the train result, right is ground trurh)
I can not find out why it happens, is it caused by the rasterization method?
Below show some of the rasterization result:( left: train render result, medium: rgb ground truth, right: rasterization mask)