Hai Li

Computer Vision and Pattern Recognition · with Liu · 2022

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hai Li trusts overall

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

  1. Richard A. Newcombe
  2. Andrew J. Davison
  3. Jürgen Sturm
  4. Brian Curless
  5. Matthias Nießner
  6. Raul Mur-Artal
  7. Olaf Kähler
  8. Lingjie Liu
  9. Thomas Whelan
  10. Christian Kerl

Papers from Hai Li's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. KinectFusion: Real-time dense surface mapping and tracking
  5. ImageNet: A large-scale hierarchical image database
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. A volumetric method for building complex models from range images
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Distinctive Image Features from Scale-Invariant Keypoints

Their papers