Kwang In Kim

Computer Vision and Pattern Recognition · with Tompkin · 2005–2018

A researcher in the Science corpus: 5 papers; trusts 510 researchers and is trusted by 245 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 110 citations into it; #2,421 of 21,575 by trust here, #6,089 by citations
• Artificial Intelligence — 43 citations into it; #21,620 of 35,345 by trust here, #32,362 by citations
• Generative Models — 31 citations into it
• Model Architectures — 13 citations into it
• Human-Computer Interaction — 12 citations into it; #1,132 of 2,253 by trust here, #2,026 by citations
• Representation & Self-Supervised Learning — 10 citations into it
• Biomedical Engineering — 9 citations into it
• Computer Graphics and Computer-Aided Design — 7 citations into it

Whom Kwang In Kim trusts overall

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

1. William T. Freeman
2. David J. Field
3. Erkki Oja
4. Geoffrey E. Hinton
5. Bernhard Schölkopf
6. Alex Krizhevsky
7. Kaiming He
8. Yoshua Bengio
9. C. Burges
10. Karen Simonyan

Who trusts Kwang In Kim overall

1. Chao Dong
2. Jia-Bin Huang
3. Jiwon Kim
4. Wei-Sheng Lai
5. Zhaowen Wang
6. Chih-Yuan Yang
7. Chen Change Loy
8. Radu Timofte
9. Ming-Hsuan Yang
10. Paul Honeine

Papers from Kwang In Kim's perspective

Ordered by how strongly the researchers Kwang In 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
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

• Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior (2010) — 993 citations
• Unsupervised Attention-guided Image to Image Translation (2018) — 323 citations
• Improving Shape Deformation in Unsupervised Image-to-Image Translation (2018) — 78 citations
• Iterative kernel principal component analysis for image modeling (2005) — 331 citations
• Real-Time Online Action Detection Forests Using Spatio-Temporal Contexts (2016) — 24 citations