Christoph Mayer
Senior Computer Vision Engineer at Scandit
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolChristoph Mayer is a Senior Computer Vision Engineer based in Zurich with nine years of experience bridging cutting‑edge research and production systems. He completed a PhD at ETH Zurich focused on visual tracking, segmentation, few‑shot detection and active learning, and spent a research stint at Google developing a multi‑object generic tracker and benchmark. At Scandit he applies this deep research background to real‑world computer vision products, while his open‑source contributions to projects like visionml/pytracking show hands‑on expertise in PyTorch tracking models and training pipelines. His track record includes industry collaborations on large‑scale detection problems and a knack for turning research prototypes into robust, deployable components.
9 years of coding experience
1 year of employment as a software developer
Master of Science (MSc), Information Technology, Master of Science (MSc), Information Technology at Eidgenössische Technische Hochschule Zürich
German, English, French
Github Skills (8)
computer-vision10
pytorch10
machine-learning10
trainings10
modeling10
resnet9
algorithm9
algorithms9
Programming languages (4)
Github contributions (5)
visionml/pytracking
Sep 2021 - Oct 2022
Visual tracking library based on PyTorch.
Role in this project:
ML Engineer
ML EngineerContributions:29 commits, 1 PR, 19 pushes in 1 year 1 month
Contributions summary:Christoph made several contributions related to the KeepTrack model and added model and results for super_dimp_simple, indicating a focus on model development. They fixed a bug in the keep_track training settings and removed unused options, suggesting they were actively involved in the model's training process. The user also integrated the ToMP tracker, demonstrating an involvement in different tracking algorithms within the project.
pytorchcomputer-visiontrackingmachine-learningvisual-tracking
2006pmach/awesome-active-learning
Nov 2019 - Jul 2022
A list of active learning methods for deep learning.
Contributions:12 commits, 2 PRs, 4 pushes in 2 years 8 months
deep-learning
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