Kun Fu

Computer Vision and Pattern Recognition · IEEE International Conference on Computer Vision · 2013–2023

A researcher in the Science corpus: 14 papers; trusts 808 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

Whom Kun Fu trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Alex Krizhevsky
  4. Geoffrey E. Hinton
  5. David G. Lowe
  6. Yoshua Bengio
  7. Yann LeCun
  8. Ilya Sutskever
  9. Christian Szegedy
  10. Andrew Zisserman

Who trusts Kun Fu overall

  1. Xue Yang
  2. Gong Cheng
  3. Rodrigo Caye Daudt
  4. Zhenwei Shi
  5. Wentong Li
  6. Jian Ding
  7. Wen Qian
  8. Yanfei Zhong
  9. Junchi Yan
  10. Yuan Yuan

Papers from Kun Fu's perspective

Ordered by how strongly the researchers Kun Fu 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. ImageNet: A large-scale hierarchical image database
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. Attention is All you Need (Neural Information Processing Systems)
  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