| Full name | ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation |
| Description | reimplementation based from https://github.com/e-lab/ENet-training |
| Publication title | ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation |
| Publication authors | Re-implementation of Adam Paszke, Abhishek Chaurasia, Sangpil Kim, Eugenio Culurciello |
| Publication URL | https://arxiv.org/abs/1606.02147 |
| Input Data Types | Uses Color Uses 2D |
| Programming language(s) | pytorch |
| Hardware | GTX 1080 |
| Submission creation date | 13 Jul, 2018 |
| Last edited | 17 Jul, 2018 |
| Last uploaded | 13 Jul, 2018 |