The primary purpose of this project is to implement the 3D object detection pipeline introduced in "3D Bounding Box Estimation Using Deep Learning and Geometry" paper for detecting four classes: Car, ...

Specifically, MonoCon is capable of identifying 3D objects in 2D images and placing them in a "bounding box," which effectively tells the AI the outermost edges of the relevant object.

The main challenge of monocular 3D object detection is the accurate localization of 3D center. Motivated by a new and strong observation that this challenge can be remedied by a 3D-space local-grid ...

Abstract: In this work, we propose a 3D-like bounding box to detect vehicles in RGB image based on the 2D bounding box detection. Taking advantage of key-points detection by detecting eight corners of ...

"That's one practical application. However, we're also excited about the fundamental advance of this work: that it is possible to get 3D data from 2D objects." Specifically, MonoCon is capable of ...