Pierre-André Savalle

Computer Vision and Pattern Recognition · 2012–2015

A researcher in the Science corpus: 3 papers; trusts 471 researchers and is trusted by 170 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it; #2,773 of 21,575 by trust here, #8,722 by citations
• Artificial Intelligence — 19 citations into it; #6,430 of 35,345 by trust here, #13,760 by citations
• Model Architectures — 8 citations into it; #575 of 2,278 by trust here, #1,402 by citations
• Optimization & Training — 6 citations into it
• Aerospace Engineering — 5 citations into it

Whom Pierre-André Savalle trusts overall

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

1. Ross B. Girshick
2. Alex Krizhevsky
3. Kaiming He
4. Geoffrey E. Hinton
5. Robert Tibshirani
6. Ilya Sutskever
7. Yann LeCun
8. Karen Simonyan
9. Navneet Dalal
10. Jitendra Malik

Who trusts Pierre-André Savalle overall

1. Liang-Chieh Chen
2. Gong Cheng
3. George Papandreou
4. Iasonas Kokkinos
5. José Manuel Álvarez
6. Gauthier Gidel
7. Shaoqing Ren
8. Wei Jin
9. Mark Sandler
10. Mathieu Salzmann

Papers from Pierre-André Savalle's perspective

Ordered by how strongly the researchers Pierre-André Savalle 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. Gradient-based learning applied to document recognition
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. 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

• Modeling local and global deformations in Deep Learning: Epitomic convolution, Multiple Instance Learning, and sliding window detection (2015) — 200 citations
• Deformable Part Models with CNN Features (2014) — 50 citations
• Estimation of Simultaneously Sparse and Low Rank Matrices (2012) — 212 citations