Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/TRI-ML/DDAD
Dense Depth for Autonomous Driving (DDAD) dataset.
https://github.com/TRI-ML/DDAD
Last synced: about 2 months ago
JSON representation
Dense Depth for Autonomous Driving (DDAD) dataset.
- Host: GitHub
- URL: https://github.com/TRI-ML/DDAD
- Owner: TRI-ML
- License: other
- Created: 2020-03-24T18:36:34.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2021-05-12T02:15:47.000Z (about 3 years ago)
- Last Synced: 2024-01-28T11:10:52.157Z (5 months ago)
- Language: Python
- Size: 12.5 MB
- Stars: 464
- Watchers: 33
- Forks: 58
- Open Issues: 11
Lists
- awesome-robotic-tooling - DDAD - A new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions. (Datasets / Sensor and Acuator Interfaces)
- awesome-robotic-tooling - DDAD - A new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions. (Datasets / Sensor and Acuator Interfaces)
- awesome-rgbd-datasets - DDAD - H2 LIDAR |SOR, and SOE |Driving |Color, Deph |Instance Segmentation |150 scenes (12650 frames) |2020/2021 | (RGB-D Datasets <a id="list" class="anchor" href="#list" aria-hidden="true"><span class="octicon octicon-link"></span></a>)