Seungyong Lee

Computer Vision and Pattern Recognition · 2007–2018

A researcher in the Science corpus: 4 papers; trusts 722 researchers and is trusted by 227 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 100 citations into it; #2,495 of 21,575 by trust here, #7,176 by citations
• Media Technology — 34 citations into it; #227 of 3,621 by trust here, #839 by citations
• Artificial Intelligence — 23 citations into it
• Model Architectures — 15 citations into it
• Generative Models — 13 citations into it
• Aerospace Engineering — 10 citations into it
• Computational Mechanics — 9 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Seungyong Lee trusts overall

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

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

Who trusts Seungyong Lee overall

1. Jin-shan Pan
2. Michael Hirsch
3. Li Xu
4. Fahad Lateef
5. Hao Chen
6. Ayan Chakrabarti
7. Zhenyu Zhang
8. Lin-Zhuo Chen
9. Chaoqiang Zhao
10. Daniel Seichter

Papers from Seungyong Lee's perspective

Ordered by how strongly the researchers Seungyong 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Fast motion deblurring (2009) — 1,265 citations
• SRFeat: Single Image Super-Resolution with Feature Discrimination (2018) — 187 citations
• RDFNet: RGB-D Multi-level Residual Feature Fusion for Indoor Semantic Segmentation (2017) — 335 citations
• Coherent line drawing (2007) — 338 citations