RobotP: A Benchmark Dataset for 6D Object Pose Estimation
Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, due to the inherent difficulty of data collection....
Main Authors: | Honglin Yuan, Tim Hoogenkamp, Remco C. Veltkamp |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/4/1299 |
Similar Items
-
A Human Kinetic Dataset and a Hybrid Model for 3D Human Pose Estimation
by: Wang, Jianquan
Published: (2020) -
Object Detection for Sweeping Robots in Home Scenes (ODSR-IHS): A Novel Benchmark Dataset
by: Yong Lv, et al.
Published: (2021-01-01) -
A Benchmark Dataset and Deep Learning-Based Image Reconstruction for Electrical Capacitance Tomography
by: Jin Zheng, et al.
Published: (2018-10-01) -
MacaquePose: A Novel “In the Wild” Macaque Monkey Pose Dataset for Markerless Motion Capture
by: Rollyn Labuguen, et al.
Published: (2021-01-01) -
Representativeness of variation benchmark datasets
by: Gerard C. P. Schaafsma, et al.
Published: (2018-11-01)