The Google team behind Objectron, then, developed a toolset that allowed annotators to label 3D bounding boxes (i.e., rectangular borders) for objects using a split-screen view to display 2D video ...

Generic object detection and tracking are fundamental and challenging tasks in computer vision. For 2D object detection, IMOU proposes an algorithm framework upon structural re-parameterization ...

Facebook AI Research and Google’s DeepMind have also made 2D to 3D AI, but DIB-R is one of the first neural or deep learning architectures that can take 2D images and then predict several key 3D ...

They say online media is going to be 3D, starting with e-tailing. Where can a merchant get that multi-dimensional content? They have 2D pictures, and they have physical objects. Occasionally there ...

NVIDIA explains that early NeRF models don't take too long to produce results either. It only takes them a few minutes to render a 3D scene, even if the subject in some of the images is obstructed ...

So first his system renders a 3D reconstruction of the 2D image in very low resolution. You can still get a lot from that — for example, that the outer third of the whole volume appears to be empty.

It scores 57.15% high-order tracking accuracy (HOTA) for multi-object tracking of pedestrian, 82.08% (HOTA) for multi-object tracking of car, and 82.77% (Moderate) for 2D object detection of ...