Loic Landrieu

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 211 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it
• Computational Mechanics — 13 citations into it; #1,543 of 10,001 by trust here, #2,032 by citations
• Geology — 13 citations into it; #96 of 687 by trust here, #189 by citations
• Artificial Intelligence — 12 citations into it
• Environmental Engineering — 12 citations into it; #539 of 5,479 by trust here, #1,138 by citations
• Aerospace Engineering — 8 citations into it
• Model Architectures — 7 citations into it
• 3D Vision & Pose — 5 citations into it

Whom Loic Landrieu trusts overall

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

1. Geoffrey E. Hinton
2. Jimmy Ba
3. Alex Krizhevsky
4. Karen Simonyan
5. Kaiming He
6. Diederik P. Kingma
7. Yoshua Bengio
8. Yuri Boykov
9. Yann LeCun
10. Andrew Zisserman

Who trusts Loic Landrieu overall

1. Andres Milioto
2. Ishan Misra
3. Charles Ruizhongtai Qi
4. Jens Behley
5. Zhiyuan Zhang
6. Tiago Cortinhal
7. Xu Yan
8. Hengshuang Zhao
9. Weixiao Gao
10. Xinlong Wang

Papers from Loic Landrieu's perspective

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

Their papers

• Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs (2017) — 1,463 citations