Ren-Cang Li

Computer Vision and Pattern Recognition · with Jiang · 2020

A researcher in the Science corpus: 1 paper; trusts 75 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Artificial Intelligence — 10 citations into it
• Generative Models — 7 citations into it
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Ren-Cang Li trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Karen Simonyan
4. Andrew Zisserman
5. Yuezun Li
6. Geoffrey E. Hinton
7. Sergey Ioffe
8. Alex Krizhevsky
9. Sepp Hochreiter
10. Christian Szegedy

Papers from Ren-Cang Li's perspective

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

Their papers

• DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection (2020) — 617 citations