Yanbei Chen

Computer Vision and Pattern Recognition · with Zhu · 2017–2022

A researcher in the Science corpus: 3 papers; trusts 1,072 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 244 citations into it; #7,264 of 21,575 by trust here, #9,435 by citations
• Artificial Intelligence — 190 citations into it; #21,064 of 35,345 by trust here, #25,809 by citations
• Representation & Self-Supervised Learning — 138 citations into it; #2,125 of 3,145 by trust here, #2,910 by citations
• Generative Models — 23 citations into it
• Signal Processing — 23 citations into it
• Multimodal Learning — 20 citations into it
• Optimization & Training — 17 citations into it
• Model Architectures — 15 citations into it

Whom Yanbei Chen trusts overall

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

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

Who trusts Yanbei Chen overall

1. Lu Liu
2. Alexander Hermans
3. Xiaobin Chang
4. Guangrun Wang
5. Hao Yang
6. Chunfeng Song
7. M. Sarfraz
8. Yifan Sun
9. Jing Xu
10. Eric Arazo

Papers from Yanbei Chen's perspective

Ordered by how strongly the researchers Yanbei Chen 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

• Person Re-identification by Deep Learning Multi-scale Representations (2017) — 419 citations
• Semi-supervised Deep Learning with Memory (2018) — 70 citations
• Semi-Supervised and Unsupervised Deep Visual Learning: A Survey (2022) — 210 citations