Cristian Canton-Ferrer

Computer Vision and Pattern Recognition · arXiv.org · 2016–2023

A researcher in the Science corpus: 8 papers; trusts 652 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 141 citations into it; #7,610 of 21,575 by trust here, #5,116 by citations
• Artificial Intelligence — 135 citations into it; #33,325 of 35,345 by trust here, #1,928 by citations
• Natural Language Processing — 43 citations into it
• Evaluation & Benchmarks — 36 citations into it
• Safety, Robustness & Interpretability — 31 citations into it
• Generative Models — 24 citations into it
• Model Architectures — 19 citations into it
• Information Systems — 16 citations into it

Whom Cristian Canton-Ferrer trusts overall

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

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

Who trusts Cristian Canton-Ferrer overall

1. Jie Gui
2. Håkon Hukkelås
3. Kai-Hong Wang
4. Tiziano Portenier
5. Samuel Schulter
6. Weiyue Wang
7. John Giorgi
8. Marcella Cornia
9. Fabio Poletto
10. Zhenan Sun

Papers from Cristian Canton-Ferrer's perspective

Ordered by how strongly the researchers Cristian Canton-Ferrer 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. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Llama 2: Open Foundation and Fine-Tuned Chat Models (2023) — 17,670 citations
• Learning by Tracking: Siamese CNN for Robust Target Association (2016) — 449 citations
• The DeepFake Detection Challenge Dataset (2020) — 323 citations
• SalGAN: Visual Saliency Prediction with Generative Adversarial Networks (2017) — 432 citations
• Training deep networks for facial expression recognition with crowd-sourced label distribution (2016) — 869 citations
• Eye In-painting with Exemplar Generative Adversarial Networks (2017) — 117 citations
• The Deepfake Detection Challenge (DFDC) Preview Dataset (2019) — 663 citations
• Hate Speech in Pixels: Detection of Offensive Memes towards Automatic Moderation (2019) — 96 citations