Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation
Our predictions for the KITTI Tracking sequence 19 with true positives (green), false positives (red), and false negatives (blue). Because these labels come in all shapes, you need to specify a ...
Abstract: Counting objects in crowded scenes remains a challenge to computer vision. The current deep learning based approach often formulate it as a Gaussian density regression problem. Such a ...
Abstract: Mapping and planning are fundamental to robotic navigation in unknown environments. This work introduces a probabilistic framework that combines Gaussian processes (GPs) for 2.5D object ...
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