Real-time probabilistic object detection of household objects
The video demonstrates a real-time probabilistic object detection, which returns uncertainty estimates of the predictions from deep neural networks. The key technology herein is a sparse Gaussian Processes with the so-called the Neural Tangent Kernel, which can provide uncertainty estimates of neural network predictions fast and reliably. Concretely, we show that an object detector can not only "know the known" objects, but also can "know the unknown" objects by providing confidence measures for both object classes and their 2D location in an image. The live demonstration took place at the 5th Annual Conference on Robot Learning in November of 2021.
License:
CC-BY 3.0
Real-time probabilistic object detection of household objects
Real-time probabilistic object detection of household objects
The video demonstrates a real-time probabilistic object detection, which returns uncertainty estimates of the predictions from deep neural networks. The key technology herein is a sparse Gaussian Processes with the so-called the Neural Tangent Kernel, which can provide uncertainty estimates of neural network predictions fast and reliably. Concretely, we show that an object detector can not only "know the known" objects, but also can "know the unknown" objects by providing confidence measures for both object classes and their 2D location in an image. The live demonstration took place at the 5th Annual Conference on Robot Learning in November of 2021.
License:
CC-BY 3.0
Credit: DLR (CC BY-NC-ND 3.0)
Duration:00:02:05