David William Murray
Computer Vision and Pattern Recognition · 2007–2016
A researcher in the Science corpus: 6 papers; trusts 249 researchers and is trusted by 533 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 73 citations into it; #1,766 of 21,575 by trust here, #2,536 by citations
- Aerospace Engineering — 60 citations into it; #43 of 6,421 by trust here, #293 by citations
- 3D Vision & Pose — 17 citations into it
- Geology — 16 citations into it; #9 of 687 by trust here, #55 by citations
- Robotics & Control — 9 citations into it
- Computer Graphics and Computer-Aided Design — 8 citations into it; #1,554 of 1,584 by trust here, #843 by citations
- Environmental Engineering — 5 citations into it
Whom David William Murray trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Georg S. W. Klein
- Jianbo Shi
- Andrew J. Davison
- Edward Rosten
- John F. Canny
- Richard A. Newcombe
- Andrew Zisserman
- Andrea Vedaldi
- David Nistér
Who trusts David William Murray overall
- Hauke Strasdat
- Andrew J. Davison
- José M. M. Montiel
- Richard A. Newcombe
- Georg S. W. Klein
- Raul Mur-Artal
- Stephan Weiss
- Jakob J. Engel
- Christian Forster
- Markus Achtelik
Papers from David William Murray's perspective
Ordered by how strongly the researchers David William Murray trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Distinctive Image Features from Scale-Invariant Keypoints
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Parallel Tracking and Mapping for Small AR Workspaces (2007) — 4,755 citations
- Improving the Agility of Keyframe-Based SLAM (2008) — 404 citations
- Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction (2015) — 213 citations
- Real-Time Large-Scale Dense 3D Reconstruction with Loop Closure (2016) — 134 citations
- Parallel Tracking and Mapping on a camera phone (2009) — 624 citations
- Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices (2015) — 322 citations