Mao Ye

Computer Vision and Pattern Recognition · with Zhu · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 288 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 54 citations into it; #12,147 of 21,575 by trust here, #11,721 by citations
• Human-Computer Interaction — 23 citations into it; #1,136 of 2,253 by trust here, #1,440 by citations
• Artificial Intelligence — 19 citations into it
• Biomedical Engineering — 14 citations into it
• 3D Vision & Pose — 8 citations into it
• Efficiency & Compression — 6 citations into it
• Model Architectures — 5 citations into it

Whom Mao Ye trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Yoshua Bengio
4. Alex Krizhevsky
5. Jimmy Ba
6. Kaiming He
7. Christian Szegedy
8. Jonathan Tompson
9. Diederik P. Kingma
10. Ross B. Girshick

Who trusts Mao Ye overall

1. Thomas Verelst

Papers from Mao Ye's perspective

Ordered by how strongly the researchers Mao Ye 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Fast Human Pose Estimation (2018) — 283 citations
• Distribution-Aware Coordinate Representation for Human Pose Estimation (2019) — 527 citations