Sung-Hoon Yoon

Computer Vision and Pattern Recognition · 2021–2023

A researcher in the Science corpus: 4 papers; trusts 328 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 116 citations into it
• Generative Models — 100 citations into it
• Artificial Intelligence — 98 citations into it
• Signal Processing — 54 citations into it
• Statistical and Nonlinear Physics — 26 citations into it
• Probabilistic & Bayesian Methods — 15 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Optimization & Training — 8 citations into it

Whom Sung-Hoon Yoon trusts overall

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

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

Papers from Sung-Hoon Yoon's perspective

Ordered by how strongly the researchers Sung-Hoon 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Perception Prioritized Training of Diffusion Models (2022) — 401 citations
• BigVGAN: A Universal Neural Vocoder with Large-Scale Training (2022) — 483 citations
• Improving Visual Prompt Tuning for Self-supervised Vision Transformers (2023) — 81 citations
• PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior (2021) — 123 citations