S. Orts-Escolano

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 379 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 277 citations into it
• Artificial Intelligence — 85 citations into it
• Generative Models — 61 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it

Whom S. Orts-Escolano trusts overall

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

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

Papers from S. Orts-Escolano's perspective

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

Their papers

• Advances in Neural Rendering (2021) — 551 citations
• A Review on Deep Learning Techniques for Video Prediction (2020) — 319 citations