Company Tabnine
A company-mode backend for TabNine, the all-language autocompleter: https://tabnine.com/
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Dcgan Completion.tensorflow | 1,245 | 7 years ago | 28 | other | Python | |||||
| Image Completion with Deep Learning in TensorFlow | ||||||||||
| Company Tabnine | 674 | 7 months ago | 19 | mit | Emacs Lisp | |||||
| A company-mode backend for TabNine, the all-language autocompleter: https://tabnine.com/ | ||||||||||
| Tabnine Intellij | 485 | 4 months ago | 32 | mit | Kotlin | |||||
| Jetbrains IDEs client for TabNine. Compatible with all IntelliJ-based IDEs. https://plugins.jetbrains.com/plugin/12798-tabnine | ||||||||||
| Self Supervised Depth Completion | 418 | 3 years ago | 25 | mit | Python | |||||
| ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera" | ||||||||||
| Sparse Depth Completion | 372 | 2 years ago | 1 | other | Python | |||||
| Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) | ||||||||||
| Dfnet | 213 | a year ago | other | Python | ||||||
| :art: Deep Fusion Network for Image Completion - ACMMM 2019 | ||||||||||
| Scancomplete | 199 | 3 years ago | 8 | apache-2.0 | Python | |||||
| [CVPR'18] ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans | ||||||||||
| Unsupervised Depth Completion Visual Inertial Odometry | 168 | 9 months ago | other | Python | ||||||
| Tensorflow implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020) | ||||||||||
| Sgnn | 127 | 3 years ago | 3 | other | C++ | |||||
| [CVPR'20] SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans | ||||||||||
| Imagecompletion_incompletedata | 110 | 6 years ago | 2 | mit | Python | |||||
| Image completion network using incomplete data | ||||||||||
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