Sen Liu

Computer Vision and Pattern Recognition · with Li · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 238 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 88 citations into it
• Media Technology — 20 citations into it
• Computer Graphics and Computer-Aided Design — 9 citations into it
• Model Architectures — 8 citations into it
• Computational Mechanics — 5 citations into it

Whom Sen Liu trusts overall

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

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

Papers from Sen Liu's perspective

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

Their papers

• Progressive Image Inpainting with Full-Resolution Residual Network (2019) — 118 citations
• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• Region Normalization for Image Inpainting (2019) — 205 citations