Efficient 3D Feature Learning for Real-Time Awareness

This extended abstract discusses the current methods and work progress on sampling large-scale point cloud datasets with semantics and reconstructing 3D objects from sparse inputs. In particular, we describe a proposed meta sampling strategy to quickly adapt sampling to multiple tasks and potential methods to improve multi-modal reconstruction. These methods could benefit immensely in creating in-depth situational awareness for challenging missions and rescues.