Survey of 6D pose and shape estimation
Survey of 6D pose and shape estimation
RGB-D-Based Categorical Object Pose and Shape Estimation: Methods, Datasets, and Evaluation
arXiv paper abstract https://arxiv.org/abs/2301.08147
arXiv PDF paper https://arxiv.org/pdf/2301.08147.pdf
GitHub https://github.com/roym899/pose_and_shape_evaluation
Recently, various methods for 6D pose and shape estimation of objects at a per-category level have been proposed.
This work provides an overview of the field in terms of methods, datasets, and evaluation protocols.
First, an overview of existing works and their commonalities and differences is provided. Second, … take a critical look at the predominant evaluation protocol, including metrics and datasets.
… propose a new set of metrics, contribute new annotations for the Redwood dataset, and evaluate state-of-the-art methods in a fair comparison.
The results indicate that existing methods do not generalize well to unconstrained orientations and are actually heavily biased towards objects being upright.
… provide an easy-to-use evaluation toolbox with well-defined metrics, methods, and dataset interfaces, which allows evaluation and comparison with various state-of-the-art approaches …
Stay up to date. Subscribe to my posts https://morrislee1234.wixsite.com/website/contact
Web site with my other posts by category https://morrislee1234.wixsite.com/website
LinkedIn https://www.linkedin.com/in/morris-lee-47877b7b
