Wonjun Yoon

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 296 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it
• Artificial Intelligence — 73 citations into it
• Representation & Self-Supervised Learning — 38 citations into it
• Generative Models — 9 citations into it
• Optimization & Training — 9 citations into it
• Model Architectures — 5 citations into it

Whom Wonjun Yoon trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Mingsheng Long
6. Diederik P. Kingma
7. Yann LeCun
8. Ilya Sutskever
9. Ross B. Girshick
10. Christian Szegedy

Papers from Wonjun Yoon's perspective

Ordered by how strongly the researchers Wonjun Yoon 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. ImageNet Large Scale Visual Recognition Challenge
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Reducing Domain Gap by Reducing Style Bias (2021) — 471 citations
• Reducing Domain Gap via Style-Agnostic Networks (2019) — 66 citations