4 papers
WeightCLIP: Aligning Datasets and Models for Weight Space Learning
Aron Asefaw, Konstantinos Tzevelekakis, Damian Falk +2
Weight space learning aims to learn representations of neural network (NN) weights, enabling different downstream tasks. Existing approaches show promising performance, but lacking…
Correcting and Quantifying Systematic Errors in 3D Box Annotations for Autonomous Driving
Alexandre Justo Miro, Ludvig af Klinteberg, Bogdan Timus +5
Accurate ground truth annotations are critical to supervised learning and evaluating the performance of autonomous vehicle systems. These vehicles are typically equipped with activ…
SSF: Sparse Long-Range Scene Flow for Autonomous Driving
Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez +3
Scene flow enables an understanding of the motion characteristics of the environment in the 3D world. It gains particular significance in the long-range, where object-based percept…
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets
Ajinkya Khoche, Aron Asefaw, Alejandro Gonzalez +3
Data annotation in autonomous vehicles is a critical step in the development of Deep Neural Network (DNN) based models or the performance evaluation of the perception system. This…