Christos Sagonas

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 4 papers; trusts 153 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it; #8,816 of 21,575 by trust here, #8,205 by citations
• Signal Processing — 24 citations into it; #3,205 of 7,572 by trust here, #3,673 by citations

Whom Christos Sagonas trusts overall

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

1. Xiangxin Zhu
2. Iain Matthews
3. Deva Ramanan
4. Jason M. Saragih
5. Pedro F. Felzenszwalb
6. Simon Baker
7. Geoffrey E. Hinton
8. Ralph Gross
9. Paul A. Viola
10. David Cristinacce

Who trusts Christos Sagonas overall

1. Stefanos P. Zafeiriou
2. Adrian Bulat
3. Georgios Tzimiropoulos
4. Stylianos Moschoglou
5. Yue Wu
6. George Trigeorgis
7. Xuanyi Dong
8. Wei Shen
9. Shaoqing Ren
10. Jiankang Deng

Papers from Christos Sagonas's perspective

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

Their papers

• A Semi-automatic Methodology for Facial Landmark Annotation (2013) — 422 citations
• AgeDB: The First Manually Collected, In-the-Wild Age Database (2017) — 877 citations
• (2013) 300 Faces in-the-Wild Challenge: the first facial landmark localization challenge. In: 2013 IEEE International (2017)
• Image and Vision Computing (2016)