We wish you a Merry Christmas and a happy new year.
We are happy to announce that our work Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery has been accepted to the 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Our work Safe Resetless Reinforcement Learning: Enhancing Training Autonomy with Risk-Averse Agents has been accepted at the Twelfth International Workshop on Assistive Computer Vision and Robotics (ACVR). The source code is available on github.
The “Institut für Informationsverarbeitung” (Institute for Information Processing) is the home of machine learning at the Leibniz University Hannover. We focus on three main research directions, namely (I) computer vision & representation learning, (II) signal processing & -coding and (III) automated machine learning. Our methods range from deep learning, automated machine learning, reinforcement learning, image analysis, remote sensing and compression of audio, image, video as well as DNA to biomedical data. Our efforts are directed towards making efficient use of multi-modal and high dimensional data for reliable predictions, ultimately supporting end-users, developers and decision makers in a vast range of applications.
Since the foundation in 1973, the institute holds a strong tradition of cultivating connections to industry partners and jointly developing solutions to automatically process and harness information. Some of the developed methodology were successfully spun-off commercially as for instance with driver assistance modules, cochlear implants or component testing. The institute is also well known for being actively involved in the standardization of MP3, MPEG-2, AVC (H.264), HEVC (H.265) as well as MPEG-G.
Do you want to join us? We have open positions.
"As an AI enthusiast pursuing a PhD, TNT provides me with an ideal opportunity to follow my passion by working in an experienced and highly motivated team under the guidance of supportive supervisors. At TNT, you will be offered enough freedom and resources to pursue your innovative ideas and shape your research in the way you want. In addition, working on challenging but interesting research questions and projects in a cooperative and supportive atmosphere here at TNT has allowed me to develop myself both personally and professionally."
