CoProU-VO Wins GCPR 2025 Best Paper Award

The paper “CoProU-VO: Combining Projected Uncertainty for End-to-End Unsupervised Monocular Visual Odometry” by MCML Director Daniel Cremers and Junior Members Weirong Chen and Johannes Meier, together with Jingchao Xie, Oussema Dhaouadi, and Jacques Kaiser received the Best Paper Award at GCPR 2025.

Their work presents CoProU-VO, an end-to-end unsupervised visual odometry framework that propagates and combines uncertainty across temporal frames to improve robustness in dynamic scenes. Built on vision transformer backbones, it jointly learns depth, uncertainty, and camera poses, achieving state-of-the-art performance on KITTI and nuScenes datasets.

Congratulations to the team on this outstanding achievement!

Check out the full paper: