Multi-Frame Video Super-Resolution Using Convolutional Neural Networks

@inproceedings{Greaves2016MultiFrameVS,
  title={Multi-Frame Video Super-Resolution Using Convolutional Neural Networks},
  author={Alex S. Greaves},
  year={2016}
}
Video super-resolution remains a challenging problem despite being a very active area of research. Even with huge strides made with single-image super-resolution, multiframe techniques, which utilize multiple frames in improving the quality of a given frame, have yet to fully take advantage of the power of deep learning. We propose a HR for multi-frame super-resolution that outputs a higher resolution version of a given frame using pixel information from adjacent frames in the video. Unlike… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 22 REFERENCES

Super Resolution From A Single Image

VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Video Super-Resolution via Deep Draft-Ensemble Learning

  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • 2015
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

Image Super-Resolution Using Deep Convolutional Networks

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2014
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

Anchored Neighborhood Regression for Fast Example-Based Super-Resolution

  • 2013 IEEE International Conference on Computer Vision
  • 2013
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

and K

G. Hinton, N. Srivastava
  • Swersky. Lecture6.5 - rmsprop
  • 2012
VIEW 2 EXCERPTS
HIGHLY INFLUENTIAL

and K

G. Hinton, N. Srivastava
  • Swersky. Lecture6.5 - rmsprop
  • 2012
VIEW 2 EXCERPTS
HIGHLY INFLUENTIAL

Deep Networks for Image Super-Resolution with Sparse Prior

  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • 2015
VIEW 2 EXCERPTS

Handling motion blur in multi-frame super-resolution

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

Image scaling using deep convolutional neural networks

N. Tasfi
  • 2015
VIEW 1 EXCERPT