Junhyun Lee

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 84 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it; #13,466 of 21,575 by trust here, #8,296 by citations
• Artificial Intelligence — 45 citations into it; #21,667 of 35,345 by trust here, #16,771 by citations
• Graph Learning — 28 citations into it
• Model Architectures — 13 citations into it
• Molecular Biology — 9 citations into it
• Statistical and Nonlinear Physics — 5 citations into it; #5,662 of 10,127 by trust here, #3,284 by citations

Whom Junhyun Lee trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Yann LeCun
5. Alex Krizhevsky
6. Oriol Vinyals
7. Kaiming He
8. Ilya Sutskever
9. Jimmy Ba
10. Max Welling

Who trusts Junhyun Lee overall

1. Filippo Maria Bianchi
2. Ekagra Ranjan
3. Lan Wei
4. Anton Tsitsulin
5. Davide Bacciu
6. Aneeshan Sain
7. Yingmin Wu
8. Seongjun Yun
9. Jie Zhou
10. Jianan Zhao

Papers from Junhyun Lee's perspective

Ordered by how strongly the researchers Junhyun Lee 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Self-Attention Graph Pooling (2019) — 1,340 citations
• HOTR: End-to-End Human-Object Interaction Detection with Transformers (2021) — 345 citations
• The Eighth Visual Object Tracking VOT2020 Challenge Results (2020) — 345 citations