Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Sparseconvnet | 1,781 | 2 months ago | 2 | July 10, 2019 | 50 | other | C++ | |||
Submanifold sparse convolutional networks | ||||||||||
Meshcnn | 1,211 | a year ago | 76 | mit | Python | |||||
Convolutional Neural Network for 3D meshes in PyTorch | ||||||||||
Medicaldetectiontoolkit | 1,167 | 4 months ago | 43 | apache-2.0 | Python | |||||
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images. | ||||||||||
Learning Deep Learning | 800 | 5 days ago | 1 | Jupyter Notebook | ||||||
Paper reading notes on Deep Learning and Machine Learning | ||||||||||
3d Convolutional Speaker Recognition | 634 | 3 years ago | 7 | apache-2.0 | Python | |||||
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification | ||||||||||
Stereo Rcnn | 517 | 3 years ago | 29 | mit | Python | |||||
Code for 'Stereo R-CNN based 3D Object Detection for Autonomous Driving' (CVPR 2019) | ||||||||||
Video Classification | 498 | 2 years ago | 26 | Jupyter Notebook | ||||||
Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101 | ||||||||||
Lifting From The Deep Release | 391 | 3 years ago | gpl-3.0 | Python | ||||||
Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image" | ||||||||||
Awesome Local Global Descriptor | 386 | 2 years ago | ||||||||
My personal note about local and global descriptor | ||||||||||
Pointconv | 351 | 3 years ago | 17 | other | Python | |||||
Infuse the 3D CNN model with the assumptions used in optical flow computaitons in a soft way through a special regularization on the filters.
We test the merit of this idea by training ConvNets from scratch on the UCF101 Human Action Recognition data set using Theano. See the report.