Kun Li

Computer Vision and Pattern Recognition · with Hou · 2014

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kun Li trusts overall

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

  1. Alexandru Cristian Telea
  2. Kaiming He
  3. Daniel Scharstein
  4. Richard Szeliski

Papers from Kun Li's perspective

Ordered by how strongly the researchers Kun Li trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Distinctive Image Features from Scale-Invariant Keypoints
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers