Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization

@inproceedings{Halder2018PerceptualCG,
  title={Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization},
  author={Shirsendu Sukanta Halder and K. De and P. Roy},
  booktitle={ACCV},
  year={2018}
}
Colours are everywhere. They embody a significant part of human visual perception. In this paper, we explore the paradigm of hallucinating colours from a given gray-scale image. The problem of colourization has been dealt in previous literature but mostly in a supervised manner involving user-interference. With the emergence of Deep Learning methods numerous tasks related to computer vision and pattern recognition have been automatized and carried in an end-to-end fashion due to the… Expand

References

SHOWING 1-10 OF 30 REFERENCES
Image De-Raining Using a Conditional Generative Adversarial Network
  • 386
  • PDF
Image-to-Image Translation with Conditional Adversarial Networks
  • 8,086
  • PDF
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
  • 4,360
  • Highly Influential
  • PDF
Colorful Image Colorization
  • 1,532
  • PDF
Let there be color!
  • 426
  • Highly Influential
  • PDF
Deep Colorization
  • 282
  • Highly Influential
  • PDF
Very Deep Convolutional Networks for Large-Scale Image Recognition
  • 47,837
  • PDF
Generative Adversarial Nets
  • 22,241
  • PDF
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  • 9,634
  • PDF
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