# TRI-ML/dd3d

<https://repo.masters-masters.com/en/repos/TRI-ML/dd3d>

[Home](https://repo.masters-masters.com/en) › [TRI-ML](https://repo.masters-masters.com/en/owners/TRI-ML) › [dd3d](https://repo.masters-masters.com/en/repos/TRI-ML/dd3d)

TRI-ML/dd3d has 493 stars on GitHub. Its RepoMasters card: Alpha tier. Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object…

| Field | Value |
| --- | --- |
| Owner | [TRI-ML](https://repo.masters-masters.com/en/owners/TRI-ML) |
| Stars | 493 |
| Forks | 74 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2021 |
| Topics | deep-learning, pytorch, computer-vision |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [TRI-ML/dd3d](https://github.com/TRI-ML/dd3d) |

## Repository

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park\*, Rares Ambrus\*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.