Detecting 3D objects with multi-modality sensors ( i.e., LiDAR and camera) is regarded as a fundamental task in real-world scenes. For accurate object detection, data from different modalities are utilized to provide complementary knowledge, like accurate positions from point clouds and rich context from images.

W e only accept 1 out of 20 papers that do not cite any other paper from our own journal.

We initiate the study of a variant of the classic online speed scaling problem, in which machine learning predictions about the future can be integrated naturally.

The industry practice has been moving to embedding based retrieval (EBR).