A large-scale hierarchical multi-view RGB-D object dataset

@article{Lai2011ALH,
  title={A large-scale hierarchical multi-view RGB-D object dataset},
  author={Kevin Lai and Liefeng Bo and Xiaofeng Ren and Dieter Fox},
  journal={2011 IEEE International Conference on Robotics and Automation},
  year={2011},
  pages={1817-1824}
}
Over the last decade, the availability of public image repositories and recognition benchmarks has enabled rapid progress in visual object category and instance detection. Today we are witnessing the birth of a new generation of sensing technologies capable of providing high quality synchronized videos of both color and depth, the RGB-D (Kinect-style) camera. With its advanced sensing capabilities and the potential for mass adoption, this technology represents an opportunity to dramatically… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 789 CITATIONS, ESTIMATED 32% COVERAGE

A survey on Deep Learning Advances on Different 3D Data Representations.

Eman Ahmed, Alexandre Saint, +5 authors Bjorn Ottersten
  • 2019
VIEW 27 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Are we done with object recognition? The iCub robot's perspective

VIEW 6 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

A Multi-Modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2018
VIEW 11 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Group Collaborative Representation for Image Set Classification

  • International Journal of Computer Vision
  • 2018
VIEW 9 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Multimodal Deep Domain Adaptation

VIEW 16 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

SHARING LEARNED MODELS BETWEEN HETEROGENEOUS ROBOTS: AN IMAGE DRIVEN INTERPRETATION

Isha Rahul Potnis, Cynthia Matuszek, Vidya Niketan
  • 2018
VIEW 14 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

3D compositional hierarchies for object categorization

VIEW 12 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Feature learning for RGB-D data

VIEW 15 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2010
2019

CITATION STATISTICS

  • 215 Highly Influenced Citations

  • Averaged 111 Citations per year over the last 3 years

References

Publications referenced by this paper.
SHOWING 1-10 OF 24 REFERENCES

A discriminatively trained, multiscale, deformable part model

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

LabelMe: A Database and Web-Based Tool for Image Annotation

  • International Journal of Computer Vision
  • 2005
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

ImageNet: A large-scale hierarchical image database

  • CVPR 2009
  • 2009
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Using stereo for object recognition

  • 2010 IEEE International Conference on Robotics and Automation
  • 2010
VIEW 2 EXCERPTS

3D generic object categorization, localization and pose estimation

  • 2007 IEEE 11th International Conference on Computer Vision
  • 2007
VIEW 1 EXCERPT

Efficient estimation of accurate maximum likelihood maps in 3D

  • 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems
  • 2007
VIEW 2 EXCERPTS

Similar Papers

Loading similar papers…