Comments (1)
Hi @brahami14 , all models in Google Drive are trained on the pure training set with corresponding config files (only large model on SemanticKITTI use instance augmentation). To gain the higher performance on SemanticKITTI, we use trained models to generate pseudo labels on its validation set, and fine-tune on these labels.
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Related Issues (20)
- inference time of 2DPASS (4scale-64dimension)
- Problems that arise during training
- Dataset Nuscenes HOT 1
- link dataset nuscenses HOT 1
- class noise
- Intensity HOT 1
- about pretrained model HOT 4
- use of intensity in 2DPASS
- When I swapped the 3D network for my own, some problems occurred
- multi-scales
- SPVCNN-nuscenes
- Running Inferences on Real-Time Data
- pre-trained model in Table 2 HOT 4
- the sacle of the 3dconv
- difference betwe paper and code about modali fuse HOT 1
- Size mismatch for pretrained model
- Segmentation fault(core dumped)
- ValueError: Input must be 1- or 2-d. HOT 1
- some issues about the idfference between the paper and the code HOT 1
- About the trainingTime
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from 2dpass.