Huibing Wang

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 250 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 83 citations into it
• Media Technology — 37 citations into it
• Artificial Intelligence — 11 citations into it
• Computational Mechanics — 5 citations into it

Whom Huibing Wang trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. David G. Lowe
4. Geoffrey E. Hinton
5. Ross B. Girshick
6. Diederik P. Kingma
7. Karen Simonyan
8. Piotr Doll'ar
9. Yann LeCun
10. Ilya Sutskever

Papers from Huibing Wang's perspective

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

Their papers

• Learning to predict crisp boundaries (2018) — 291 citations
• NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results (2020) — 190 citations