license: apache-2.0
SweepNet Dataset
This repository contains three datasets used in SweepNet. One dataset comprised of 20,000 sweep surfaces for neural sweeper training and two datasets used in quantitative evaluations. All datasets are preprocessed.
Neural Sweeper Dataset
We created 20,000 sweep surface samples to train the neural sweeper, please refer to the supplementary material for the training details. We provided sweep surfaces with 3, 4 and 5 control points, structured as follows:
neuralSweeperData/
├── control_point_i/
│ ├── sweep_surface_index/
│ │ ├── parameterse.txt # sweep surface parameters
│ │ ├── bspline.ply #visualized sweeping axis
│ │ ├── sample_profile.obj #visualized profile
│ │ ├── result_sweep.ply # sweep surface
│ │ ├── manifold_points.npy # key points on the sweep surface
│ │ ├── sweep_occupancy_v1.npy # Occupancy field of the sweep surface
GC-Object Dataset
We sampled 50 generalised cylinder featured objects from internet and prior works OreX, GCD. We provide processed 3D models here. Please consider cite us and the prior works if you find the dataset useful.
GC_objects/
├── model name/
│ ├── oracle.obj # Oracle 3D model (not the input)
│ ├── voxel_64_mc.off # 3D model reconstructed from input voxel
│ ├── skeletal_prior.ply # Model skeletons
│ ├── model_surface_point_cloud.ply # Surface point cloud for point cloud input modality
├── test_names.npz # List of all model names
├── voxel2pc.hdf5 # Model voxels and occupancy field used for training
├── ae_voxel_points_samples.hdf5 # Model voxels and occupancy field used *only* for testing
Quadrupeds Dataset
We use quadrupeds dataset from Tulsiani et al. to benchmark SweepNet. We provide the processed data here, please cite us if you used our processed data.
quadrupeds/
├── model name/
│ ├── oracle.obj # Oracle 3D model (not the input)
│ ├── skeletal_prior.ply # Model skeletons
│ ├── model_surface_point_cloud.ply # Surface point cloud for point cloud input modality
├── test_names.npz # List of all model names
├── voxel2pc.hdf5 # Model voxels and occupancy field used for training
├── ae_voxel_points_samples.hdf5 # Model voxels and occupancy field used *only* for testing