Alejandro Newell

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 5 papers; trusts 1,057 researchers and is trusted by 3,661 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 174 citations into it; #547 of 21,575 by trust here, #1,427 by citations
• Artificial Intelligence — 81 citations into it; #6,124 of 35,345 by trust here, #8,007 by citations
• Representation & Self-Supervised Learning — 42 citations into it
• Computational Mechanics — 36 citations into it
• Geology — 30 citations into it
• Aerospace Engineering — 20 citations into it
• 3D Vision & Pose — 18 citations into it
• Biomedical Engineering — 13 citations into it; #46 of 10,734 by trust here, #595 by citations

Whom Alejandro Newell trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Diederik P. Kingma
7. Yoshua Bengio
8. Christian Szegedy
9. Jitendra Malik
10. Ilya Sutskever

Who trusts Alejandro Newell overall

1. Xingyi Zhou
2. Jia Deng
3. Hei Law
4. Wanli Ouyang
5. Bin Xiao
6. Georgios Pavlakos
7. Liang-Chieh Chen
8. Adrian Bulat
9. Xiaogang Wang
10. Xuanyi Dong

Papers from Alejandro Newell's perspective

Ordered by how strongly the researchers Alejandro Newell 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Stacked Hourglass Networks for Human Pose Estimation (2016) — 5,506 citations
• Associative Embedding: End-to-End Learning for Joint Detection and Grouping (2016) — 995 citations
• Pixels to Graphs by Associative Embedding (2017) — 242 citations
• How Useful Is Self-Supervised Pretraining for Visual Tasks? (2020) — 151 citations
• Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline (2021) — 308 citations