Xiangtao Kong

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 2 papers; trusts 213 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Xiangtao Kong trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Jiwon Kim
  6. Yoshua Bengio
  7. Jimmy Ba
  8. Yann LeCun
  9. Ying Tai
  10. Ross B. Girshick

Papers from Xiangtao Kong's perspective

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

Their papers