Shaoxin Li

Computer Vision and Pattern Recognition · with Huang · 2020

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 Shaoxin Li trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Kaiming He (in Computer Vision and Pattern Recognition)
  4. Alex Krizhevsky (in Computer Vision and Pattern Recognition)

Papers from Shaoxin Li's perspective

Ordered by how strongly the researchers Shaoxin Li 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. Curriculum learning
  4. FaceNet: A unified embedding for face recognition and clustering
  5. Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments
  6. Gradient-based learning applied to document recognition
  7. DeepFace: Closing the Gap to Human-Level Performance in Face Verification
  8. Going deeper with convolutions
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers