6D Pose Estimation for Textureless Objects on RGB Frames using Multi-View Optimization
Author:
Affiliation:
1. University of Toronto Institute for Aerospace Studies and Robotics Institute
2. Epson Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160529.pdf?arnumber=10160529
Reference53 articles.
1. Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd
2. OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation
3. Robust 6D Object Pose Estimation by Learning RGB-D Features
4. PVN3D: A Deep Point-Wise 3D Keypoints Voting Network for 6DoF Pose Estimation
5. Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes;hinterstoisser;Asian Conference on Computer Vision,2012
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1. Multi-View Metal Parts Pose Estimation Based on a Single Camera;Sensors;2024-05-25
2. Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. A Method for Unseen Object Six Degrees of Freedom Pose Estimation Based on Segment Anything Model and Hybrid Distance Optimization;Electronics;2024-02-16
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