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hello, Im a staff of a research institute, I read your paper and find its a great model for indoor instance segmentation. when I try to apply it to outdoor and road pointcloud data which box(space size) of scene is about 200~300meter, It runs several problem. the fatal one is when I set scale as big as indoor you set 50(voxel size 1/50), cuda memory will out, and when I run with scale = 1, the result will performance bad and low pixel. I try to crop our scene in a samll room, but lost Semantic information and performance not well neither. could you give some advice , if I solve this problem and apply in outdoor data, Im happy to share it on github if you are willing too. Thanks
The text was updated successfully, but these errors were encountered:
hello, Im a staff of a research institute, I read your paper and find its a great model for indoor instance segmentation. when I try to apply it to outdoor and road pointcloud data which box(space size) of scene is about 200~300meter, It runs several problem. the fatal one is when I set scale as big as indoor you set 50(voxel size 1/50), cuda memory will out, and when I run with scale = 1, the result will performance bad and low pixel. I try to crop our scene in a samll room, but lost Semantic information and performance not well neither. could you give some advice , if I solve this problem and apply in outdoor data, Im happy to share it on github if you are willing too. Thanks
The text was updated successfully, but these errors were encountered: