Li Song

Computer Vision and Pattern Recognition · with Shen · 2021

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 Li Song trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Keith Rayner (in Cognitive Science & Psychology)
  3. James M. Rehg (in Computer Vision and Pattern Recognition)
  4. Antonio Torralba (in Computer Vision and Pattern Recognition)

Papers from Li Song's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. ImageNet: A large-scale hierarchical image database
  3. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
  4. Automatic photo pop-up
  5. Learning to predict where humans look (IEEE International Conference on Computer Vision)
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Unsupervised Monocular Depth Estimation with Left-Right Consistency
  8. Fine-Grained Head Pose Estimation Without Keypoints (2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW))
  9. ImageNet classification with deep convolutional neural networks
  10. Deeper Depth Prediction with Fully Convolutional Residual Networks

Their papers