I am a PhD student at the computer vision group supervised by Prof. Daniel Cremers. I received a Master's degree in Mathematics for Science and Engineering and a Bachelor's degree in Engineering Science from Technical University of Munich. I have studied at Technical University Munich (TUM), Federal Institute of Technology Zürich (ETH), University of Notre Dame in South Bend (ND) and École Polytechnique in Paris (X). I did my Master's thesis at Artisense and did an internship at BMW's autonomous driving division.
I am interested, among others, in Computer Vision, Machine Learning and Autonomous Driving. I enjoy passing on knowledge and worked as a teaching assistant for close to ten courses, e.g. The Evolution of Motion Estimation and Real-time 3D Reconstruction, Computer Vision II: Multiple View Geometry, and Numerical Treatment of Ordinary Differential Equations. In my free time I like climbing.
You can send an email to firstname.lastname@example.org, or follow me on twitter.
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
Lukas Koestler*, Nan Yang*, Niclas Zeller, Daniel Cremers
TANDEM combines photometric tracking and deep multi-view stereo depth estimation into a monocular dense SLAM algorithm. Using depth maps rendered from the incrementally-built TSDF model improves tracking robustness.
Learning 3D Vehicle Detection without 3D Bounding Box Labels
Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers
By predicting object meshes and employing differentiable rendering, we define loss functions based on depth maps, segmentation masks, and ego- and object-motion, which are generated by pre-trained, off-the-shelf networks.