Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

Understand

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics.

• Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features.
• Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects.
• A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing.