PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

@article{Xiang2017PoseCNNAC,
  title={PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes},
  author={Yu Xiang and Tanner Schmidt and Venkatraman Narayanan and Dieter Fox},
  journal={ArXiv},
  year={2017},
  volume={abs/1711.00199}
}
Estimating the 6D pose of known objects is important for robots to interact with the real world. The problem is challenging due to the variety of objects as well as the complexity of a scene caused by clutter and occlusions between objects. In this work, we introduce PoseCNN, a new Convolutional Neural Network for 6D object pose estimation. PoseCNN estimates the 3D translation of an object by localizing its center in the image and predicting its distance from the camera. The 3D rotation of the… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 36 REFERENCES

Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images

  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • 2015
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2016
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

6-DoF object pose from semantic keypoints

  • 2017 IEEE International Conference on Robotics and Automation (ICRA)
  • 2017
VIEW 2 EXCERPTS

Real-Time Seamless Single Shot 6D Object Pose Prediction

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • 2017
VIEW 3 EXCERPTS

SegICP: Integrated deep semantic segmentation and pose estimation

  • 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2017
VIEW 1 EXCERPT