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3D object detection is vital as it would enable us to capture objects' sizes,orientation, and position in the world. As a result, we would be able to usethis 3D detection in real-world applications such as Augmented Reality (AR),self-driving cars, and robotics which perceive the world the same way we do ashumans. Monocular 3D Object Detection is the task to draw 3D bounding boxaround objects in a single 2D RGB image. It is localization task but withoutany extra information like depth or other sensors or multiple images. Monocular3D object detection is an important yet challenging task. Beyond thesignificant progress in image-based 2D object detection, 3D understanding ofreal-world objects is an open challenge that has not been explored extensivelythus far. In addition to the most closely related studies.

Monocular 3D Object Detection using Multi-Stage Approaches with Attention and Slicing aided hyper inference