Peng Wang

Computer Vision and Pattern Recognition · with Han · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 177 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 55 citations into it
• Artificial Intelligence — 51 citations into it
• Model Architectures — 17 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Optimization & Training — 9 citations into it

Whom Peng Wang trusts overall

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

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

Papers from Peng Wang's perspective

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

Their papers

• Multi-Label Image Recognition With Graph Convolutional Networks (2019) — 1,230 citations
• Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification (2021) — 298 citations
• Anisotropic Convolutional Networks for 3D Semantic Scene Completion (2020) — 187 citations