Face Attribute Prediction with classification CNN

@article{Zhong2016FaceAP,
  title={Face Attribute Prediction with classification CNN},
  author={Yang Zhong and Josephine Sullivan and Haibo Li},
  journal={ArXiv},
  year={2016},
  volume={abs/1602.01827}
}
Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavorable conditions. Given the success of convolutional neural network (CNN) in image classification, the high-level CNN feature as an intuitive and reasonable choice has been widely utilized for this problem. In this paper, however, we consider the mid-level CNN features as an… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-5 OF 5 CITATIONS

A method of facial wearable items recognition

  • 2017 Chinese Automation Congress (CAC)
  • 2017
VIEW 3 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

Learning Multifunctional Binary Codes for Both Category and Attribute Oriented Retrieval Tasks

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 1 EXCERPT
CITES RESULTS

Deep face attributes recognition using spatial transformer network

  • 2016 IEEE International Conference on Information and Automation (ICIA)
  • 2016
VIEW 2 EXCERPTS
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 19 REFERENCES

Deep Learning Face Attributes in the Wild

  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • 2014
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Deep Learning Face Representation from Predicting 10,000 Classes

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

FaceNet: A unified embedding for face recognition and clustering

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2015
VIEW 2 EXCERPTS

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
  • 2014
VIEW 1 EXCERPT

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 1 EXCERPT

From generic to specific deep representations for visual recognition

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • 2014
VIEW 1 EXCERPT

Going deeper with convolutions

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2014
VIEW 1 EXCERPT