Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors

Understand

We present a method to infer 3D pose and shape of vehicles from a single image.

• To tackle this ill-posed problem, we optimize two-scale projection consistency between the generated 3D hypotheses and their 2D pseudo-measurements.
• Specifically, we use a morphable wireframe model to generate a fine-scaled representation of vehicle shape and pose.
• To reduce its sensitivity to 2D landmarks, we jointly model the 3D bounding box as a coarse representation which improves robustness.