Yu-Kun Lai

Computer Vision and Pattern Recognition · 2013–2022

A researcher in the Science corpus: 7 papers; trusts 617 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 198 citations into it; #10,938 of 21,575 by trust here, #10,677 by citations
• Computational Mechanics — 52 citations into it
• Artificial Intelligence — 49 citations into it
• Computer Graphics and Computer-Aided Design — 46 citations into it; #904 of 1,584 by trust here, #659 by citations
• Representation & Self-Supervised Learning — 27 citations into it
• Generative Models — 26 citations into it; #1,185 of 1,956 by trust here, #1,796 by citations
• Aerospace Engineering — 19 citations into it
• Model Architectures — 17 citations into it

Whom Yu-Kun Lai trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Karen Simonyan
5. David G. Lowe
6. Diederik P. Kingma
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Yu-Kun Lai overall

1. Weihao Xia
2. Sung Woo Park
3. Jie Gui
4. Tao Yang
5. Yujiu Yang
6. Taekyung Kim
7. Yonggan Fu

Papers from Yu-Kun Lai's perspective

Ordered by how strongly the researchers Yu-Kun Lai 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. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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

• NeRF-Editing: Geometry Editing of Neural Radiance Fields (2022) — 299 citations
• CartoonGAN: Generative Adversarial Networks for Photo Cartoonization (2018) — 402 citations
• Recognition From Web Data: A Progressive Filtering Approach (2018) — 41 citations
• APDrawingGAN: Generating Artistic Portrait Drawings From Face Photos With Hierarchical GANs (2019) — 176 citations
• An Efficient LSTM Network for Emotion Recognition From Multichannel EEG Signals (2020) — 311 citations
• IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition (2019) — 472 citations
• Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) — 715 citations