CVPR Daily - Wednesday

“ Acquisition systems often produce 3D point clouds and images, and we want to be able to combine the information from each modality because they are complementary, ” he explains. “ The point clouds describe the scene’s geometry, and the images describe other things like the texture and the context. We want to use information from both. We’re not the first ones to do it, but we’re the first to learn multi- view aggregation for large scenes. ” The team wanted to work at a large scale, with scans of cities and buildings rather than a small point cloud of an isolated chair, for example, where you only have pictures of that object. However, manipulating the information that connects the point cloud and images at a large scale is difficult. “ I had to spend a lot of time coding to efficiently manipulate the link between images and point clouds and never break this connection through the whole pipeline, ” Damien tells us. “ You must ensure that each 3D point is properly connected to the corresponding pixels. It’s very tricky. ” 21 DAILY CVPR Wednesday Damien Robert