Baopu Li

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 210 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 105 citations into it
• Artificial Intelligence — 55 citations into it
• Model Architectures — 20 citations into it
• Optimization & Training — 12 citations into it

Whom Baopu Li 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. Yann LeCun
7. X. Zhang
8. Diederik P. Kingma
9. Shaoqing Ren
10. Karen Simonyan

Papers from Baopu Li's perspective

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

Their papers

• GLiT: Neural Architecture Search for Global and Local Image Transformer (2021) — 104 citations
• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer (2020) — 349 citations
• MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation (2021) — 87 citations