KGNv2: Separating Scale and Pose Prediction for Keypoint-Based 6-DoF Grasp Synthesis on RGB-D Input
Author:
Affiliation:
1. School of Electrical and Computer Engineering, and the Institute for Robotics and Intelligent Machines, Georgia Institute of Technology,Atlanta,GA
Funder
NSF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10341341/10341342/10342514.pdf?arnumber=10342514
Reference52 articles.
1. Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
2. Real-World Multiobject, Multigrasp Detection
3. GKNet: Grasp keypoint network for grasp candidates detection
4. Faster R-CNN: Towards real-time object detection with region proposal networks;Ren;Advances in Neural Information Processing Systems,2015
5. Objects as points;Zhou;arXiv preprint,2019
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1. TFENet: Topological Feature Extraction Network for 6D Object Pose Estimation;2023 China Automation Congress (CAC);2023-11-17
2. Real-Time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Prediction;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01
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