Daniel DeTone

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 412 researchers and is trusted by 180 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 71 citations into it; #2,739 of 21,575 by trust here, #5,333 by citations
• Aerospace Engineering — 41 citations into it; #363 of 6,421 by trust here, #782 by citations
• Artificial Intelligence — 15 citations into it
• 3D Vision & Pose — 10 citations into it
• Model Architectures — 10 citations into it
• Media Technology — 9 citations into it
• Geology — 8 citations into it

Whom Daniel DeTone trusts overall

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

1. David G. Lowe
2. Karen Simonyan
3. Alex Krizhevsky
4. Andrew Zisserman
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. Kaiming He
8. Ross B. Girshick
9. Yann LeCun
10. Tsung-Yi Lin

Who trusts Daniel DeTone overall

1. Paul-Edouard Sarlin
2. Jiayi Ma
3. Xingyu Jiang
4. Zachary Teed
5. Vincent Leroy
6. Zixin Luo
7. Philipp Lindenberger
8. Eduard Trulls
9. Ignacio Rocco
10. Christoph Mayer

Papers from Daniel DeTone's perspective

Ordered by how strongly the researchers Daniel DeTone 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• SuperPoint: Self-Supervised Interest Point Detection and Description (2017) — 3,557 citations
• SuperGlue: Learning Feature Matching With Graph Neural Networks (2019) — 2,839 citations
• Deep Image Homography Estimation (2016) — 518 citations