Sangmin Bae

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 129 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Artificial Intelligence — 22 citations into it

Whom Sangmin Bae trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Diederik P. Kingma
7. Yann LeCun
8. Ilya Sutskever
9. Karen Simonyan
10. X. Zhang

Papers from Sangmin Bae's perspective

Ordered by how strongly the researchers Sangmin Bae 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. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• MixCo: Mix-up Contrastive Learning for Visual Representation (2020) — 95 citations