Mao Ye

Computer Vision and Pattern Recognition · with Ren · 2011–2017

A researcher in the Science corpus: 3 papers; trusts 351 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 119 citations into it; #21,476 of 21,575 by trust here, #7,852 by citations
• Artificial Intelligence — 41 citations into it
• Human-Computer Interaction — 25 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• 3D Vision & Pose — 7 citations into it
• Biophysics — 7 citations into it

Whom Mao Ye trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. David G. Lowe
4. Pedro F. Felzenszwalb
5. Juergen Gall
6. Gabriele Fanelli
7. Yann LeCun
8. Andrew Zisserman
9. Navneet Dalal
10. Kaiming He

Who trusts Mao Ye overall

1. Meng Ding
2. Fei Han
3. Pichao Wang
4. Srinath Sridhar
5. Jun Liu
6. Javier Romero
7. Michalis Vrigkas
8. Raviteja Vemulapalli
9. Chen Qian
10. Marco F. Cusumano-Towner

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. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Accurate 3D pose estimation from a single depth image (2011) — 272 citations
• A Survey on Human Motion Analysis from Depth Data (2013) — 243 citations
• Do Convolutional Neural Networks Learn Class Hierarchy? (2017) — 232 citations