Pierre Fernandez

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 4 papers; trusts 316 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 311 citations into it
• Artificial Intelligence — 244 citations into it
• Representation & Self-Supervised Learning — 133 citations into it
• Generative Models — 49 citations into it

Whom Pierre Fernandez trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Alex Krizhevsky
5. Prafulla Dhariwal
6. Yoshua Bengio
7. Alex Nichol
8. Yann LeCun
9. Jia Deng
10. Ilya Sutskever

Papers from Pierre Fernandez's perspective

Ordered by how strongly the researchers Pierre Fernandez 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• DINOv2: Learning Robust Visual Features without Supervision (2023) — 9,372 citations
• A Cookbook of Self-Supervised Learning (2023) — 398 citations
• Seamless: Multilingual Expressive and Streaming Speech Translation (2023) — 299 citations
• The Stable Signature: Rooting Watermarks in Latent Diffusion Models (2023) — 417 citations