Jinkyu Kim

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 464 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 96 citations into it; #16,050 of 21,575 by trust here, #9,305 by citations
• Artificial Intelligence — 71 citations into it; #26,036 of 35,345 by trust here, #13,760 by citations
• Representation & Self-Supervised Learning — 31 citations into it
• Generative Models — 19 citations into it
• Signal Processing — 14 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 8 citations into it

Whom Jinkyu Kim trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Alex Krizhevsky
5. Sepp Hochreiter
6. Yoshua Bengio
7. Matthew D. Zeiler
8. Karen Simonyan
9. Ilya Sutskever
10. Yann LeCun

Who trusts Jinkyu Kim overall

1. Gesina Schwalbe
2. Li Chen
3. Sarah Wiegreffe
4. D. Gunning
5. Chenhao Tan
6. Jianyu Chen
7. Ana I. Maqueda
8. Aditya Chattopadhyay
9. Giulia Vilone
10. Bettina Finzel

Papers from Jinkyu Kim's perspective

Ordered by how strongly the researchers Jinkyu 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Textual Explanations for Self-Driving Vehicles (2018) — 460 citations
• Sound-Guided Semantic Image Manipulation (2021) — 54 citations
• SelfReg: Self-supervised Contrastive Regularization for Domain Generalization (2021) — 349 citations
• Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention (2017) — 377 citations