Gi-Cheon Kang

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 255 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it; #13,110 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 33 citations into it
• Multimodal Learning — 22 citations into it; #702 of 1,211 by trust here, #1,033 by citations
• Natural Language Processing — 13 citations into it
• Graph Learning — 9 citations into it
• Model Architectures — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Gi-Cheon Kang trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Jimmy Ba
5. Yoshua Bengio
6. Alex Krizhevsky
7. Shaoqing Ren
8. Ross B. Girshick
9. Ilya Sutskever
10. Yann LeCun

Who trusts Gi-Cheon Kang overall

1. Van-Quang Nguyen
2. Tianhao Yang
3. Sungjin Park
4. Yi Zhu
5. Zhengjun Zha
6. Masanori Suganuma
7. Hyounghun Kim
8. Taesun Whang
9. Hanwang Zhang
10. Shubham Agarwal

Papers from Gi-Cheon Kang's perspective

Ordered by how strongly the researchers Gi-Cheon Kang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Dual Attention Networks for Visual Reference Resolution in Visual Dialog (2019) — 80 citations
• DialGraph: Sparse Graph Learning Networks for Visual Dialog (2020) — 4 citations