Ke Wang

Orcid: 0000-0002-8272-455X

Affiliations:
  • University of North Carolina, Department of Computer Science, Chapel Hill, NC, USA


According to our database1, Ke Wang authored at least 13 papers between 2014 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2018
Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery.
PhD thesis, 2018

Physics-Inspired Garment Recovery from a Single-View Image.
ACM Trans. Graph., 2018

Retweet Wars: Tweet Popularity Prediction via Dynamic Multimodal Regression.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

2017
Efficient video collection association using geometry-aware Bag-of-Iconics representations.
IPSJ Trans. Comput. Vis. Appl., 2017

Single View Parametric Building Reconstruction from Satellite Imagery.
Proceedings of the 2017 International Conference on 3D Vision, 2017

Fast and Accurate Satellite Multi-view Stereo Using Edge-Aware Interpolation.
Proceedings of the 2017 International Conference on 3D Vision, 2017

2016
Detailed Garment Recovery from a Single-View Image.
CoRR, 2016

Efficient joint stereo estimation and land usage classification for multiview satellite data.
Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

Bringing 3D Models Together: Mining Video Liaisons in Crowdsourced Reconstructions.
Proceedings of the Computer Vision - ACCV 2016, 2016

2015
Minimal Solvers for 3D Geometry from Satellite Imagery.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
Combining semantic scene priors and haze removal for single image depth estimation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014

Joint Object Class Sequencing and Trajectory Triangulation (JOST).
Proceedings of the Computer Vision - ECCV 2014, 2014

Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014


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