Nikos Athanasiou

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 363 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 73 citations into it; #10,194 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 28 citations into it
• Control and Systems Engineering — 16 citations into it; #3,287 of 8,257 by trust here, #1,814 by citations
• Computational Mechanics — 12 citations into it
• Generative Models — 10 citations into it
• 3D Vision & Pose — 8 citations into it
• Natural Language Processing — 7 citations into it
• Optimization & Training — 5 citations into it

Whom Nikos Athanasiou trusts overall

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

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

Who trusts Nikos Athanasiou overall

1. Kevin Qinghong Lin
2. Mingyuan Zhang
3. Zerong Zheng
4. Lijuan Wang
5. Shih-Yang Su
6. Ruilong Li
7. Guy Tevet
8. Shubham Goel
9. Wenjie Zhu
10. Chuan Guo

Papers from Nikos Athanasiou's perspective

Ordered by how strongly the researchers Nikos Athanasiou 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• VIBE: Video Inference for Human Body Pose and Shape Estimation (2019) — 1,167 citations
• BABEL: Bodies, Action and Behavior with English Labels (2021) — 348 citations