Computer Vision – Machine Learning – Robotics
We are hiring … join our team … in Prague & Paris!
Scientific objectives. The IMPACT project focuses on fundamental and applied research in computer vision, machine learning and robotics to develop machines that learn to perceive, reason, navigate and interact with complex dynamic environments. For example, people easily learn how to change a flat tire of a car or perform resuscitation by observing other people doing the same task. This involves advanced visual intelligence abilities such as interpreting sequences of human actions that manipulate objects to achieve a specific task. Currently, however, there is no artificial system with a similar level of cognitive visual competence.
Applications. Breakthrough progress in intelligent machine perception will have profound implications on our everyday lives as well as science and commerce, with smart assistive robots that automatically learn new skills from the Internet, safer cars that autonomously navigate in difficult changing conditions, or intelligent glasses that help people navigate never seen before environments.
- ELLIS is organizing an online workshop on how to tackle Covid-19 using methods of machine learning and AI.
- Our work on PLMP – Point-Line Minimal Problems in Complete Multi-View Visibility won the Best Student Paper Award at ICCV 2019. The paper is available here (pdf).
- The European Laboratory for Learning and Intelligent Systems (ELLIS) announced establishment of 17 units, including one at CIIRC CTU in Prague
- Our work on Estimating 3D Motion and Forces of Person-Object Interactions was shortlisted for Best Paper at CVPR 2019 (top 1% of submitted papers). The project page, including the paper and videos, is available here.
- Our work on Neighbourhood Consensus Networks was presented as a spotlight at NeurIPS 2018. The paper is available here.
- Recording of talk by Prof. David Fouhey (University of Michigan): “Understanding how to get to places and do things“
- Project Impact appears in the new issue of the Czech Technical University magazine Technicall (pdf, in Czech only)
- Recording of talk by Prof. Alexei Efros (UC Berkeley): “Self-supervision, Meta-supervision, Curiosity: Making Computers Study Harder”
- Two prizes awarded to Josef Šivic in 2017