Comments (1)
Thanks for the interest in our work. We'll be sharing the pre-trained models using PointNet feature extractor soon. However, feel free to train the model yourself using the PointNet codebase provided in https://github.com/WangYueFt/dgcnn/blob/master/pytorch/model.py
All the implementation details are provided in the paper.
from crosspoint.
Related Issues (20)
- the definition of loss function HOT 5
- Downstream tasks 3D Object classification HOT 3
- How did you get the 2D images corresponding to the ModelNet40, ScanObjectNN point cloud data? The content inside eval_ssl.ipynb looks incomprehensible, can you provide the original .py file code? HOT 3
- Can train_crosspoint.py train the partseg model based on ShapeNetPart? HOT 2
- What's the GPU device used during your training and finetuing? HOT 1
- About PointNetRendering Dataset
- Can't download the dataset using gdown HOT 2
- How did you use the t-sne visualization feature and can you provide the source code? HOT 1
- distributed training for CrossPoint HOT 4
- relatively large performance gap on ScanObjectNN HOT 4
- It seems that the pretrain model you provide has gap on modelnet40 HOT 3
- what variant do we use in few-shot learning on ScanObjectNN? HOT 2
- Definition of the dgcnn_seg model
- About the pointcloud visualization software in Fig.2 HOT 1
- Availability of checkpoint
- What's the specific environment of this code?
- RuntimeError: CUDA error: invalid device ordinal
- The distributed implementation of CrossPoint is available here ! HOT 1
- null
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from crosspoint.