Yunseok Jang

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 594 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 119 citations into it; #7,159 of 21,575 by trust here, #4,750 by citations
• Artificial Intelligence — 84 citations into it; #13,225 of 35,345 by trust here, #7,346 by citations
• Multimodal Learning — 42 citations into it
• Natural Language Processing — 40 citations into it
• Generative Models — 21 citations into it
• Model Architectures — 15 citations into it
• Optimization & Training — 9 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Yunseok Jang trusts overall

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

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

Who trusts Yunseok Jang overall

1. Jie Lei
2. Chenyou Fan
3. Pin Jiang
4. Zhou Zhao
5. Junbin Xiao
6. Linjie Li
7. Junyeong Kim
8. Licheng Yu
9. Yueting Zhuang
10. Yahong Han

Papers from Yunseok Jang's perspective

Ordered by how strongly the researchers Yunseok Jang 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. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering (2017) — 700 citations
• Diversity-Sensitive Conditional Generative Adversarial Networks (2019) — 223 citations
• Video Question Answering with Spatio-Temporal Reasoning (2019) — 68 citations