Cvxpnpl Alternatives
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Nerfstudio | 7,811 | 10 months ago | 524 | apache-2.0 | Python | |||||
| A collaboration friendly studio for NeRFs | ||||||||||
| Vrn | 4,368 | 3 years ago | 4 | mit | MATLAB | |||||
| :man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression" | ||||||||||
| 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. | ||||||||||
| Awesome Hand Pose Estimation | 2,872 | a year ago | 3 | Python | ||||||
| Awesome work on hand pose estimation/tracking | ||||||||||
| Alicevision | 2,752 | 10 months ago | 69 | other | C++ | |||||
| Photogrammetric Computer Vision Framework | ||||||||||
| 3d Resnets Pytorch | 2,677 | 4 years ago | 120 | mit | Python | |||||
| 3D ResNets for Action Recognition (CVPR 2018) | ||||||||||
| 3ddfa_v2 | 2,554 | a year ago | 90 | mit | Python | |||||
| The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020. | ||||||||||
| Habitat Sim | 2,239 | 10 months ago | 156 | mit | C++ | |||||
| A flexible, high-performance 3D simulator for Embodied AI research. | ||||||||||
| Simulator | 2,029 | 2 years ago | 625 | other | C# | |||||
| A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles | ||||||||||
| Objectron | 1,958 | 2 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 | ||||||||||
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