Right now, the direction in the autonomous driving field is going into an end-to-end pipeline, meaning you get data from the sensor, you try to process it, maybe you do it in an early stage, you fuse the data right away when it goes out of the sensor. You can also do it in a later stage, meaning that you process the data from different sensors independently and then you fuse it. “This depends on how you approach the thing,” Lorenzo declares, “but you get the data, you process it and then after fusion you specialize on the task you want. The trend now is going end-to-end. So from the data to the output, which is the action of physical driving.” Filippo thinks that this work solves the problem on one side and it opens new directions for new research on the other side: “I think both are true - we solve the problem by demonstrating that our method performs better than previous methods. Our model’s generalization ability is such that you can train your model with one camera and one LiDAR and then during the evaluation stage you can use another camera, a different camera. And things keep working! But we also open a new direction, because no one before us has focused on the bird's eye view technique for calibration.” 10 DAILY WACV Monday Oral Presentation
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