Alexandre Robicquet

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 230 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 73 citations into it; #4,619 of 21,575 by trust here, #3,848 by citations
• Artificial Intelligence — 66 citations into it; #25,089 of 35,345 by trust here, #6,422 by citations
• Ocean Engineering — 19 citations into it; #1,872 of 3,193 by trust here, #518 by citations
• Model Architectures — 13 citations into it; #1,162 of 2,278 by trust here, #604 by citations
• Control and Systems Engineering — 11 citations into it
• Reinforcement Learning — 9 citations into it
• Generative Models — 6 citations into it

Whom Alexandre Robicquet trusts overall

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

1. Stefano Pellegrini
2. Brian D. Ziebart
3. Geoffrey E. Hinton
4. Alex Graves
5. Yoshua Bengio
6. Wongun Choi
7. Alex Krizhevsky
8. Diederik P. Kingma
9. Ilya Sutskever
10. Kaiming He

Who trusts Alexandre Robicquet overall

1. Amir Sadeghian
2. Karttikeya Mangalam
3. Javad Amirian
4. Takuma Yagi
5. Julian Bock
6. Ye Lyu
7. Tianpei Gu
8. Alexandre Alahi
9. Gioele Ciaparrone
10. Kris M. Kitani

Papers from Alexandre Robicquet's perspective

Ordered by how strongly the researchers Alexandre Robicquet trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Social LSTM: Human Trajectory Prediction in Crowded Spaces (2016) — 3,459 citations
• Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes (2016) — 946 citations
• A guide to deep learning in healthcare (2019) — 4,405 citations