As my first project at [MIT Driverless](https://driverless.mit.edu/), my task was meant to find the visual explaination of the CNN-based object detection model that perception team is using, the [YOLOv3](https://arxiv.org/pdf/1804.02767.pdf). After reviewing the results, we concluded that the network has its most attention on the bottom part of the object(traffic cone), and in some cases the margin between cone and ground.