DFKI researchers win two awards in the Object Pose Estimation Challenge (BOP Challenge, ECCV 2022)



Yongzhi Su, Praveen Nathan and Jason Rambach, scientists from the Augmented Reality (Augmented Vision) research department at DFKI, received together their 1st place award in the prestigious BOP Challenge 2022 in the categories Overall Best Segmentation Method and The Best BlenderProc-Trained Segmentation Method.

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The BOP benchmark and challenge addresses the problem of 6-degree-of-freedom object pose estimation, which is of great importance for many applications such as robot grasping or augmented reality. This year, the BOP challenge was held within the “Recovering 6D Object Pose” Workshop at the European Conference on Computer Vision (ECCV) in Tel Aviv, Israel. A total award of $4000 was distributed among the winning teams of the BOP challenge, donated by Meta Reality Labs and Niantic.

The awards were received by Dr. Jason Rambach on behalf of the DFKI Team and a short presentation of the method followed. The winning method was based on the CVPR 2022 paper “ZebraPose”.

ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation
Yongzhi Su, Mahdi Saleh, Torben Fetzer, Jason Raphael Rambach, Nassir Navab, Benjamin Busam, Didier Stricker, Federico Tombari


The winning approach was develop by a team led by DFKI AV, with contributing researchers from TU Munich and Zhejiang University. 

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German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz