Jun Cheng

Computer Vision and Pattern Recognition · with Tao · 2015–2020

A researcher in the Science corpus: 2 papers; trusts 136 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it
• Generative Models — 17 citations into it
• Aerospace Engineering — 6 citations into it

Whom Jun Cheng trusts overall

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

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

Who trusts Jun Cheng overall

1. Weihao Xia
2. Yujiu Yang
3. Hao Wang
4. Hui Ye
5. Shulan Ruan
6. Jing-Hao Xue
7. Ming Tao
8. Guosheng Lin
9. Baoyuan Wu

Papers from Jun Cheng's perspective

Ordered by how strongly the researchers Jun Cheng 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• RiFeGAN: Rich Feature Generation for Text-to-Image Synthesis From Prior Knowledge (2020) — 124 citations
• Local structure preserving discriminative projections for RGB-D sensor-based scene classification (2015) — 28 citations