StyleLess layer: Improving robustness for real-world driving
Julien Rebut,Andrei Bursuc,Patrick Pérez,Julien Rebut,Andrei Bursuc,Patrick Pérez
Deep Neural Networks (DNNs) are a critical component for self-driving vehicles. They achieve impressive performance by reaping information from high amounts of labeled data. Yet, the full complexity of the real world cannot be encapsulated in the training data, no matter how big the dataset, and DNNs can hardly generalize to unseen conditions. Robustness to various image corruptions, caused by cha...
