Heewon Kim

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 349 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 100 citations into it; #3,955 of 21,575 by trust here, #2,381 by citations
• Media Technology — 51 citations into it; #338 of 3,621 by trust here, #109 by citations
• Artificial Intelligence — 21 citations into it
• Model Architectures — 17 citations into it
• Optimization & Training — 7 citations into it

Whom Heewon Kim trusts overall

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

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

Who trusts Heewon Kim overall

1. Kai Zhang
2. Radu Timofte
3. Yulun Zhang
4. Saeed Anwar
5. Andreas Lugmayr
6. Jingyun Liang
7. Luc Van Gool
8. Xintao Wang
9. Jinjin Gu
10. Namhyuk Ahn

Papers from Heewon Kim's perspective

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

Their papers

• Enhanced Deep Residual Networks for Single Image Super-Resolution (2017) — 7,355 citations
• NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results (2017) — 1,901 citations
• Channel Attention Is All You Need for Video Frame Interpolation (2020) — 369 citations