Md Zafar Anwar — accepted AI-conference papers

2025

MapDiffusion: Generative Diffusion for Vectorized Online HD Map Construction and Uncertainty Estimation in Autonomous Driving

Thomas Monninger, Zihan Zhang, Zhipeng Mo, Md Zafar Anwar, Steffen Staab, Sihao Ding

IROS 2025

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 vector decoder predicts a vectorized map representation from the latent BEV grid. However, traditional map construction mod

Cited by 9 Source ↗Scholar ↗

2024

TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation

Thomas Monninger, Vandana Dokkadi, Md Zafar Anwar, Steffen Staab

IROS 2024poster

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) encoders can achieve this by mapping data from individual sensors into one joint latent space. For cost-efficient camera-only…

Cited by 0 Source ↗Scholar ↗