Master thesis for self-supervised action recognition using contrastive learning
Fraunhofer IOSB is doing basic research and exploring applications for optronic sensors, ranging from light production and detection to complex assistant and autonomous systems supporting humans in a wide variety of tasks. The team »Perceptual User Interfaces« of Fraunhofer IOSB offers you a master thesis for the conceptual design and development of a self-supervised machine learning approach in the area of 3D skeleton based action recognition. In this thesis, we will research state-of-the art approaches for label-free 3D skeleton based action recognition. With a self-supervised contrastive learning approach label-free training can be achieved. The aim of this approach is a better generalization to unseen data. This thesis provides an opportunity to implement and evaluate self-supervised learning approaches in the area of action recognition. Fraunhofer IOSB is working on action recognition for human-machine interaction (HMI) in vehicle interiors.
What you will do
What you bring to the table
What you can expect
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Interested? Apply online now. We look forward to getting to know you!
If you have any questions please contact: David Lerch Phone: +49 721 6091-157 david.lerch@iosb.fraunhofer.de
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
Requisition Number: 61435 Application Deadline:
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