Ioannis A. Kakadiaris

Computer Vision and Pattern Recognition · 2000–2017

A researcher in the Science corpus: 7 papers; trusts 1,136 researchers and is trusted by 68 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 226 citations into it; #3,607 of 21,575 by trust here, #6,031 by citations
• Artificial Intelligence — 102 citations into it
• Biomedical Engineering — 37 citations into it
• Human-Computer Interaction — 33 citations into it
• Signal Processing — 20 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• 3D Vision & Pose — 13 citations into it
• Control and Systems Engineering — 11 citations into it

Whom Ioannis A. Kakadiaris trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Diederik P. Kingma
5. Kaiming He
6. Karen Simonyan
7. Yann LeCun
8. Andrew Zisserman
9. Ross B. Girshick
10. Ilya Sutskever

Who trusts Ioannis A. Kakadiaris overall

1. Ronald Poppe
2. Michael Hofmann
3. Carlos Barron
4. Alan Brunton
5. Fengliang Xu
6. Riccardo Satta
7. Michael J. Black
8. Jonathan Scholz
9. Alexandru O. Balan
10. Xiaozheng Zhang

Papers from Ioannis A. Kakadiaris's perspective

Ordered by how strongly the researchers Ioannis A. Kakadiaris 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Estimating Anthropometry and Pose from a Single Uncalibrated Image (2001) — 99 citations
• 3D Human pose estimation: A review of the literature and analysis of covariates (2016) — 331 citations
• End-to-End 3D Face Reconstruction with Deep Neural Networks (2017) — 273 citations
• Model-Based Estimation of 3D Human Motion (2000) — 201 citations
• Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach (2007) — 517 citations
• Adaptive SVM+: Learning with Privileged Information for Domain Adaptation (2017) — 25 citations
• A Review of Human Activity Recognition Methods (2015) — 538 citations