Comments (1)
Hi Shamit,
Thanks for your interest in our work. For Matterport3D experiment, we don't train at all on Matterport3D dataset, but only trained on the small crops of our synthetic room dataset. Therefore, during inference, we only require pointcloud.npz file as the input, which are the surface points.
from convolutional_occupancy_networks.
Related Issues (20)
- train on outdoor LiDAR pointcloud HOT 1
- Noise during inference
- What's the difference between "points.npz" and "pointcloud.npz"? HOT 1
- How do I retrain the model HOT 1
- Finetune for pretrained model HOT 1
- How can I generate mesh with my own point cloud data HOT 7
- RuntimeError: cannot join current thread" by running "python generate.py configs/pointcloud_crop/demo_matterport.yaml" HOT 6
- How to transform a mesh to a occupancy mat? HOT 1
- Use *.pcd file as input to inference or inference without normals HOT 1
- How to train a new model for your own dataset HOT 4
- Which config file is to run 3D Volume input?
- out of memory error HOT 1
- on my own data HOT 2
- What is the resolution of surface reconstruction ? HOT 1
- unable to download shapenet, synthetic room datasets in colab
- RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`
- what 's the difference between shape_1plane.pt and shape_3plane.pt??? HOT 1
- Question on initialized parameter values for point cloud crop generation
- pip install torch_scatter==2.0.2
- from cython.operator cimport dereference as drefεΊι
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from convolutional_occupancy_networks.