Jongwook Choi

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 444 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 63 citations into it; #3,823 of 21,575 by trust here, #4,502 by citations
• Artificial Intelligence — 34 citations into it
• Multimodal Learning — 26 citations into it; #243 of 1,211 by trust here, #389 by citations
• Natural Language Processing — 26 citations into it
• Evaluation & Benchmarks — 20 citations into it
• Model Architectures — 16 citations into it
• Generative Models — 14 citations into it; #754 of 1,956 by trust here, #865 by citations
• Optimization & Training — 12 citations into it

Whom Jongwook Choi trusts overall

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

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

Who trusts Jongwook Choi overall

1. Tianfu Wu
2. Antoine Miech
3. Jaemin Cho
4. Youngjae Yu
5. Bo Zhao
6. Jianfeng Dong
7. Tobias Hinz
8. Aditya Mogadala
9. Jiadong Liang
10. Chris Dongjoo Kim

Papers from Jongwook Choi's perspective

Ordered by how strongly the researchers Jongwook Choi 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis (2018) — 359 citations
• End-to-End Concept Word Detection for Video Captioning, Retrieval, and Question Answering (2016) — 245 citations
• Video Captioning and Retrieval Models with Semantic Attention (2016) — 46 citations