Carlos Esteves

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 3 papers; trusts 208 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 66 citations into it; #8,971 of 21,575 by trust here, #8,952 by citations
• Computational Mechanics — 29 citations into it; #5,332 of 10,001 by trust here, #3,463 by citations
• Artificial Intelligence — 23 citations into it
• Model Architectures — 23 citations into it; #1,005 of 2,278 by trust here, #1,231 by citations
• Aerospace Engineering — 13 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Carlos Esteves trusts overall

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

1. David G. Lowe
2. Kaiming He
3. Geoffrey E. Hinton
4. Yann LeCun
5. Alex Krizhevsky
6. Charles Ruizhongtai Qi
7. Karen Simonyan
8. Yoshua Bengio
9. Diederik P. Kingma
10. Pietro Perona

Who trusts Carlos Esteves overall

1. Erik J. Bekkers
2. Brandon M. Anderson
3. Taco Cohen
4. Marc Finzi
5. Risi Kondor
6. Michaël Defferrard
7. Yu-Chuan Su
8. Nathanael Perraudin
9. Maurice Weiler
10. Fanny Yang

Papers from Carlos Esteves's perspective

Ordered by how strongly the researchers Carlos Esteves 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning SO(3) Equivariant Representations with Spherical CNNs (2017) — 582 citations
• Polar Transformer Networks (2017) — 200 citations
• 3D object classification and retrieval with Spherical CNNs (2017) — 26 citations