Myeongjin Kim

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 343 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 25 citations into it; #9,412 of 21,575 by trust here, #17,258 by citations
• Artificial Intelligence — 13 citations into it; #14,639 of 35,345 by trust here, #26,682 by citations
• Evaluation & Benchmarks — 5 citations into it
• Generative Models — 5 citations into it

Whom Myeongjin Kim trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Andrew Zisserman
6. Jia Deng
7. Diederik P. Kingma
8. Ross B. Girshick
9. Yoshua Bengio
10. Yann LeCun

Who trusts Myeongjin Kim overall

1. Luke Melas-Kyriazi
2. Lukas Hoyer
3. Dengxin Dai
4. Christos Sakaridis
5. Jiahua Dong
6. Luc Van Gool
7. Arjun K. Manrai
8. Sicheng Zhao
9. Yang Cong
10. Xiangyu Yue

Papers from Myeongjin Kim's perspective

Ordered by how strongly the researchers Myeongjin Kim 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. ImageNet: A large-scale hierarchical image database
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
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

• Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation (2020) — 309 citations