pointnet2
pointnet
Our great sponsors
pointnet2 | pointnet | |
---|---|---|
2 | 1 | |
2,875 | 4,565 | |
- | - | |
0.0 | 0.0 | |
over 1 year ago | 5 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pointnet2
-
Why does trained model fail on new data?
Is this how you trained the segmentation? https://github.com/charlesq34/pointnet2
- Are the New M1 Macbooks Any Good for Deep Learning? Let’s Find Out
pointnet
-
How do I balance a pointcloud dataset without compromising it?
I am using pointnet, A neural network which directly processes point clouds and labels them on a per-point basis.
What are some alternatives?
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
ttach - Image Test Time Augmentation with PyTorch!
h-former - H-Former is a VAE for generating in-between fonts (or combining fonts). Its encoder uses a Point net and transformer to compute a code vector of glyph. Its decoder is composed of multiple independent decoders which act on a code vector to reconstruct a point cloud representing a glpyh.
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
AREnets - Tensorflow-based framework which lists attentive implementation of the conventional neural network models (CNN, RNN-based), applicable for Relation Extraction classification tasks as well as API for custom model implementation
RAFT
anime-segmentation - high-accuracy segmentation for anime character