Zihang Lai

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 519 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 88 citations into it; #9,990 of 21,575 by trust here, #14,151 by citations
• Representation & Self-Supervised Learning — 33 citations into it; #1,676 of 3,145 by trust here, #2,404 by citations
• Artificial Intelligence — 21 citations into it
• Model Architectures — 9 citations into it
• Natural Language Processing — 8 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Aerospace Engineering — 6 citations into it

Whom Zihang Lai trusts overall

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

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

Who trusts Zihang Lai overall

1. D. Epstein
2. Wenguan Wang
3. Allan Jabri
4. Xiankai Lu
5. Carl Vondrick
6. Andrew Owens
7. Tianfei Zhou
8. Alexei A. Efros
9. David J. Crandall
10. Yu-Wing Tai

Papers from Zihang Lai's perspective

Ordered by how strongly the researchers Zihang Lai 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

• Self-supervised Video Representation Learning for Correspondence Flow (2019) — 48 citations
• MAST: A Memory-Augmented Self-Supervised Tracker (2020) — 204 citations