Simon Hadfield

Computer Vision and Pattern Recognition · 2011–2020

A researcher in the Science corpus: 13 papers; trusts 733 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 322 citations into it; #6,216 of 21,575 by trust here, #2,570 by citations
• Artificial Intelligence — 87 citations into it
• Model Architectures — 38 citations into it
• Natural Language Processing — 35 citations into it
• Aerospace Engineering — 34 citations into it
• Human-Computer Interaction — 32 citations into it; #1,251 of 2,253 by trust here, #948 by citations
• Evaluation & Benchmarks — 30 citations into it
• Signal Processing — 20 citations into it

Whom Simon Hadfield trusts overall

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

1. Ivan Laptev
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Graves
5. Yann LeCun
6. Diederik P. Kingma
7. Ilya Sutskever
8. Alex Krizhevsky
9. Kaiming He
10. Cordelia Schmid

Who trusts Simon Hadfield overall

1. Pichao Wang
2. Yu Kong
3. Xiaodong Yang
4. Xi Chen
5. Kishore Reddy Konda
6. Mariano Jaimez
7. Michael Hornacek
8. Oscar Koller
9. Necati Cihan Camgöz
10. Wanqing Li

Papers from Simon Hadfield's perspective

Ordered by how strongly the researchers Simon Hadfield trusts endorse each paper. Same corpus, a different order for every researcher.

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

• The Visual Object Tracking VOT2015 Challenge Results (2015) — 901 citations
• The Visual Object Tracking VOT2014 Challenge Results (2014) — 512 citations
• The Visual Object Tracking VOT2016 Challenge Results (2016) — 773 citations
• The Visual Object Tracking VOT2017 Challenge Results (2017) — 301 citations
• The Sixth Visual Object Tracking VOT2018 Challenge Results (2018) — 797 citations
• Hollywood 3D: Recognizing Actions in 3D Natural Scenes (2013) — 106 citations
• Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation (2020) — 771 citations
• Neural Sign Language Translation (2018) — 863 citations
• Kinecting the dots: Particle based scene flow from depth sensors (2011) — 110 citations
• Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition (2016) — 98 citations
• SubUNets: End-to-End Hand Shape and Continuous Sign Language Recognition (2017) — 335 citations
• Exploring Causal Relationships in Visual Object Tracking (2015) — 15 citations
• Scene Particles: Unregularized Particle Based Scene Flow Estimation. (2013) — 29 citations