51 citations · 80 across the 12 of their papers we have counts for
4 papers · 1 filter
LidarCLIP or: How I Learned to Talk to Point Clouds
Georg Hess, Adam Tonderski, Christoffer Petersson +2
Research connecting text and images has recently seen several breakthroughs, with models like CLIP, DALL-E 2, and Stable Diffusion. However, the connection between text and other v…
Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds
Georg Hess, Johan Jaxing, Elias Svensson +3
Masked autoencoding has become a successful pretraining paradigm for Transformer models for text, images, and, recently, point clouds. Raw automotive datasets are suitable candidat…
Object Detection as Probabilistic Set Prediction
Georg Hess, Christoffer Petersson, Lennart Svensson
Accurate uncertainty estimates are essential for deploying deep object detectors in safety-critical systems. The development and evaluation of probabilistic object detectors have b…
Can Deep Learning be Applied to Model-Based Multi-Object Tracking?
Juliano Pinto, Georg Hess, William Ljungbergh +3
Multi-object tracking (MOT) is the problem of tracking the state of an unknown and time-varying number of objects using noisy measurements, with important applications such as auto…