Neill D. F. Campbell

Computer Vision and Pattern Recognition · 2008–2015

A researcher in the Science corpus: 4 papers; trusts 170 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 57 citations into it; #12,288 of 21,575 by trust here, #9,305 by citations
• Artificial Intelligence — 10 citations into it
• Aerospace Engineering — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• 3D Vision & Pose — 6 citations into it
• Computer Graphics and Computer-Aided Design — 5 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Neill D. F. Campbell trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Vladimir Kolmogorov
2. Daniel Scharstein
3. Yuri Boykov
4. Geoffrey E. Hinton
5. George Vogiatzis
6. Carlos Hernández Esteban
7. Ce Liu
8. Brian Curless
9. William T. Freeman
10. Richard Szeliski

Who trusts Neill D. F. Campbell overall

1. Yasutaka Furukawa
2. Michal Jancosek
3. Yebin Liu
4. Silvano Galliani
5. Yao Yao
6. Shahram Izadi
7. Michael Niemeyer
8. Johannes L. Schönberger
9. Mengqi Ji
10. Xiaodong Gu

Papers from Neill D. F. Campbell's perspective

Ordered by how strongly the researchers Neill D. F. Campbell trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Patch Based Synthesis for Single Depth Image Super-Resolution (2012) — 234 citations
• Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo (2008) — 447 citations
• Modeling object appearance using Context-Conditioned Component Analysis (2015) — 5 citations
• Hierarchical Subquery Evaluation for Active Learning on a Graph (2014) — 110 citations