1 citations · 1 across the 3 of their papers we have counts for
4 papers
MapDiffusion: Generative Diffusion for Vectorized Online HD Map Construction and Uncertainty Estimation in Autonomous Driving
Thomas Monninger, Zihan Zhang, Zhipeng Mo +3
Autonomous driving requires an understanding of the static environment from sensor data. Learned Bird's-Eye View (BEV) encoders are commonly used to fuse multiple inputs, and a vec…
AutoVDC: Automated Vision Data Cleaning Using Vision-Language Models
Santosh Vasa, Aditi Ramadwar, Jnana Rama Krishna Darabattula +5
Training of autonomous driving systems requires extensive datasets with precise annotations to attain robust performance. Human annotations suffer from imperfections, and multiple…
AugMapNet: Improving Spatial Latent Structure via BEV Grid Augmentation for Enhanced Vectorized Online HD Map Construction
Thomas Monninger, Md Zafar Anwar, Stanislaw Antol +2
Autonomous driving requires understanding infrastructure elements, such as lanes and crosswalks. To navigate safely, this understanding must be derived from sensor data in real-tim…
TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation
Thomas Monninger, Vandana Dokkadi, Md Zafar Anwar +1
Autonomous driving requires an accurate representation of the environment. A strategy toward high accuracy is to fuse data from several sensors. Learned Bird's-Eye View (BEV) encod…