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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Open3d | 11,955 | 2 months ago | 1,018 | other | C++ | |||||
Open3D: A Modern Library for 3D Data Processing | ||||||||||
Nerfstudio | 7,811 | a year ago | 524 | apache-2.0 | Python | |||||
A collaboration friendly studio for NeRFs | ||||||||||
Nnunet | 4,608 | 11 | a year ago | 23 | September 01, 2021 | 90 | apache-2.0 | Python | ||
Mmdetection3d | 4,497 | 1 | a year ago | 34 | October 19, 2023 | 489 | apache-2.0 | Python | ||
OpenMMLab's next-generation platform for general 3D object detection. | ||||||||||
Kaolin | 4,038 | a year ago | 3 | May 03, 2023 | 144 | apache-2.0 | Python | |||
A PyTorch Library for Accelerating 3D Deep Learning Research | ||||||||||
3ddfa | 3,243 | 3 years ago | 52 | mit | Python | |||||
The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution. | ||||||||||
3d Resnets Pytorch | 2,677 | 4 years ago | 120 | mit | Python | |||||
3D ResNets for Action Recognition (CVPR 2018) | ||||||||||
Flops Counter.pytorch | 2,606 | 5 | 19 | a year ago | 20 | October 27, 2023 | 30 | mit | Python | |
Flops counter for convolutional networks in pytorch framework | ||||||||||
3ddfa_v2 | 2,554 | 2 years ago | 90 | mit | Python | |||||
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020. | ||||||||||
Objectron | 1,958 | 3 years ago | 21 | other | Jupyter Notebook | |||||
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes |