Guillaume Couairon

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 6 papers; trusts 588 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 248 citations into it; #10,385 of 21,575 by trust here, #5,464 by citations
• Artificial Intelligence — 183 citations into it; #19,859 of 35,345 by trust here, #16,471 by citations
• Generative Models — 81 citations into it
• Multimodal Learning — 69 citations into it; #1,091 of 1,211 by trust here, #722 by citations
• Molecular Biology — 46 citations into it
• Representation & Self-Supervised Learning — 41 citations into it
• Evaluation & Benchmarks — 34 citations into it
• Meta & Continual Learning — 28 citations into it; #623 of 1,041 by trust here, #606 by citations

Whom Guillaume Couairon trusts overall

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

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

Who trusts Guillaume Couairon overall

1. Inbar Huberman-Spiegelglas
2. Jiwoo Chung
3. Chenshuang Zhang
4. Pierre Fernandez
5. Lianghua Huang
6. Chenyang Qi
7. Junyi Zhang
8. Da-Wei Zhou
9. Su Wang
10. Vladimir Kulikov

Papers from Guillaume Couairon's perspective

Ordered by how strongly the researchers Guillaume Couairon 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

• FLAVA: A Foundational Language And Vision Alignment Model (2021) — 987 citations
• DiffEdit: Diffusion-based semantic image editing with mask guidance (2022) — 779 citations
• DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion (2021) — 468 citations
• Generating functional protein variants with variational autoencoders (2020) — 210 citations
• The Stable Signature: Rooting Watermarks in Latent Diffusion Models (2023) — 417 citations
• Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar (2023) — 333 citations