Implicit Neural Scene Representations
Virtual Zoom Seminar: https://cmu.zoom.us/j/92178295543?pwd=L2dwZU5SbDY5NzZZNzZ4ZmFUclRqQT09 Abstract How we represent signals has major implications for the algorithms we build to analyze them. Today, most signals are represented discretely: Images as grids of pixels, shapes as point clouds, audio as grids of amplitudes, etc. If images weren't pixel grids - would we be using convolutional neural networks [...]
Chenfeng Tu – MSR Thesis Talk
Location: https://cmu.zoom.us/j/96696044200?pwd=MVl4aUpiZlYvYlRwRmF1SVBUeGx6Zz09 Title: On-the-fly Targetless Extrinsics Calibration For Multi-Stereo Systems Without Field-of-View Overlap Abstract: In this talk, we propose an on-the-fly extrinsics calibration method for stereo pairs lacking overlapping field of view that is robust to visual odometry errors. Multi-stereo systems are becoming increasingly popular because of their large field of view (FoV) that benefits [...]
Shuoqi Chen – MSR Thesis Talk
Zoom link: https://cmu.zoom.us/j/9608506704 Title: Towards Geometric Motion Planning for 3-link Kinematic Systems Abstract: Geometric mechanics offers a powerful mathematical framework for studying locomotion for mobile systems. Despite the well-established literature, challenges remain when using geometric mechanics to design gaits for robots made of multi-link chain; in this thesis, we look at two of them. First, [...]