Mehdi Zayene is now a senior data scientist in a consulting company in Switzerland named Effixis. He is also the first author of paper that was accepted as a poster and as a highlight at CVPR 2025. Helvipad: A Real-World Dataset for Omnidirectional Stereo Depth Estimation 18 DAILY CVPR Sunday Highlight Presentation This project started back more than three years ago, when Mehdi was still in his bachelor's studies at EPFL, École Polytechnique Fédérale de Lausanne in Switzerland. And there a professor - Alexandre Alahi - had the idea of implementing a new methos of depth detection with stereo 360 degrees cameras. Something that wasn't really existing at the time. 360 degrees cameras provide actually complete FOV and rich geometric information. Omnidirectional imaging remains still underexplored due to the lack of real world data sets, The biggest challenge was not building the deep learning AI model itself, but to collect the data set. They had to build a physical engine, a physical robot with two cameras, one LIDAR that they had to synchronize in time.
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