Computer Vision – ECCV 2018

@inproceedings{Ferrari2018ComputerV,
  title={Computer Vision – ECCV 2018},
  author={Vittorio Ferrari and Martial Hebert and Cristian Sminchisescu and Yair Weiss},
  booktitle={Lecture Notes in Computer Science},
  year={2018}
}
Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all sensory inputs. In computer vision, however, there has been relatively little exploration of hard attention, where some information is selectively ignored, in spite of the success of soft attention, where information is re-weighted and aggregated, but never filtered out. Here, we introduce a new approach for hard… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 72 REFERENCES

De-noising, stabilizing and completing 3D reconstructions on-the-go using plane priors

  • 2017 IEEE International Conference on Robotics and Automation (ICRA)
  • 2017
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Keyframe-based dense planar SLAM

  • 2017 IEEE International Conference on Robotics and Automation (ICRA)
  • 2017
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

A computationally efficient denoising and holefilling method for depth image enhancement

S. Liu, C. Chen, N. Kehtarnava
  • SPIE Conference on Real-Time Image and Video Processing,
  • 2016
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Robust RGB-D simultaneous localization and mapping using planar point features

  • Robotics and Autonomous Systems
  • 2015
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

Similar Papers

Loading similar papers…