https://challenger.ai/competition/adp2018 无人驾驶视觉感知竞赛初赛到决赛 用一个模型解决标检测和可行驶区域分割 初赛和决赛都是用的一个模型 作为basebone(resnet50-maskrcnn) + driverable branch
| Installation | Documentation | Tutorials |
GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in computer vision.
It is designed for engineers, researchers, and students to fast prototype products and research ideas based on these models. This toolkit offers four main features:
- Training scripts to reproduce SOTA results reported in research papers
- A large number of pre-trained models
- Carefully designed APIs that greatly reduce the implementation complexity
- Community supports