Kun Zhou

Computer Vision and Pattern Recognition · with Jia · 2022

A researcher in the Science corpus: 1 paper; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it
• Generative Models — 24 citations into it

Whom Kun Zhou trusts overall

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

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

Papers from Kun Zhou's perspective

Ordered by how strongly the researchers Kun Zhou 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. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• MAT: Mask-Aware Transformer for Large Hole Image Inpainting (2022) — 503 citations