Namhyuk Ahn

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 550 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 109 citations into it; #6,094 of 21,575 by trust here, #8,122 by citations
• Media Technology — 66 citations into it; #931 of 3,621 by trust here, #1,079 by citations
• Generative Models — 21 citations into it
• Artificial Intelligence — 17 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Efficiency & Compression — 8 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Namhyuk Ahn trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Chao Dong
6. Jiwon Kim
7. Ilya Sutskever
8. Ross B. Girshick
9. Yoshua Bengio
10. Yann LeCun

Who trusts Namhyuk Ahn overall

1. Radu Timofte
2. Andreas Lugmayr
3. Saeed Anwar
4. Zhihao Wang
5. Jinjin Gu
6. Wanjie Sun
7. Xiangxiang Chu
8. Jie Liu
9. Zhisheng Lu
10. Wenming Yang

Papers from Namhyuk Ahn's perspective

Ordered by how strongly the researchers Namhyuk Ahn trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Image Super-Resolution via Progressive Cascading Residual Network (2018) — 71 citations
• Fast, Accurate, and, Lightweight Super-Resolution with Cascading Residual Network (2018) — 1,424 citations
• NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results (2020) — 190 citations