Théo Moutakanni

Computer Vision and Pattern Recognition · 2023–2025

A researcher in the Science corpus: 3 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 109 citations into it

Whom Théo Moutakanni trusts overall

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

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

Papers from Théo Moutakanni's perspective

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

Their papers

• DINOv2: Learning Robust Visual Features without Supervision (2023) — 9,372 citations
• DINOv3 (2025) — 1,140 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