1 citations · 2 across the 3 of their papers we have counts for
3 papers
Robust Temporal Ensembling for Learning with Noisy Labels
Abel Brown, Benedikt Schifferer, Robert DiPietro
Successful training of deep neural networks with noisy labels is an essential capability as most real-world datasets contain some amount of mislabeled data. Left unmitigated, label…
Accurate Trajectory Prediction for Autonomous Vehicles
Michael Diodato, Yu Li, Antonia Lovjer +7
Predicting vehicle trajectories, angle and speed is important for safe and comfortable driving. We demonstrate the best predicted angle, speed, and best performance overall winning…
Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge
Antonia Lovjer, Minsu Yeom, Benedikt D. Schifferer +1
In this work we predict vehicle speed and steering angle given camera image frames. Our key contribution is using an external pre-trained neural network for segmentation. We augmen…