Kai Vetter

Computer Vision and Pattern Recognition · 2011–2017

A researcher in the Science corpus: 4 papers; trusts 87 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kai Vetter trusts overall

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

  1. David G. Lowe
  2. Lubor Ladicky
  3. Andreas Geiger
  4. Ross B. Girshick
  5. Daniel Munoz
  6. Pushmeet Kohli
  7. Joseph Tighe
  8. Geoffrey E. Hinton
  9. Yann LeCun
  10. Kaiming He

Papers from Kai Vetter's perspective

Ordered by how strongly the researchers Kai Vetter 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. Gradient-based learning applied to document recognition
  4. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  5. Distinctive Image Features from Scale-Invariant Keypoints
  6. ImageNet: A large-scale hierarchical image database
  7. Long Short-Term Memory
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers