Jianfang Hu

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 5 papers; trusts 535 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 202 citations into it; #4,777 of 21,575 by trust here, #5,620 by citations
• Artificial Intelligence — 122 citations into it; #7,299 of 35,345 by trust here, #9,465 by citations
• Biomedical Engineering — 54 citations into it
• Human-Computer Interaction — 42 citations into it
• 3D Vision & Pose — 28 citations into it
• Model Architectures — 16 citations into it
• Representation & Self-Supervised Learning — 10 citations into it; #972 of 3,145 by trust here, #1,415 by citations
• Control and Systems Engineering — 9 citations into it

Whom Jianfang Hu trusts overall

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

1. Geoffrey E. Hinton
2. Karen Simonyan
3. Alex Krizhevsky
4. Kaiming He
5. Andrew Zisserman
6. Yoshua Bengio
7. Yann LeCun
8. Zicheng Liu
9. Ross B. Girshick
10. Diederik P. Kingma

Who trusts Jianfang Hu overall

1. Jun Liu
2. Amir Shahroudy
3. Pengfei Zhang
4. Qiuhong Ke
5. G. Wang
6. Pichao Wang
7. Xionghui Wang
8. Weishi Zheng
9. Cuiling Lan
10. J. Lai

Papers from Jianfang Hu's perspective

Ordered by how strongly the researchers Jianfang Hu 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
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

• Progressive Teacher-Student Learning for Early Action Prediction (2019) — 137 citations
• Jointly Learning Heterogeneous Features for RGB-D Activity Recognition (2015) — 557 citations
• Deep Bilinear Learning for RGB-D Action Recognition (2018) — 84 citations
• Early Action Prediction by Soft Regression (2019) — 117 citations
• Real-Time RGB-D Activity Prediction by Soft Regression (2016) — 93 citations