Bingkun Bao

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 2 papers; trusts 155 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it
• Artificial Intelligence — 19 citations into it

Whom Bingkun Bao trusts overall

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

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

Papers from Bingkun Bao's perspective

Ordered by how strongly the researchers Bingkun Bao 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. GENERATIVE ADVERSARIAL NETS
10. ImageNet: A large-scale hierarchical image database

Their papers

• DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis (2020) — 308 citations
• DeblurGAN+: Revisiting blind motion deblurring using conditional adversarial networks (2020) — 74 citations