Martin Rünz

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 242 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

Whom Martin Rünz trusts overall

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

  1. Kaiming He
  2. Shaoqing Ren
  3. Thomas Whelan
  4. Ross B. Girshick
  5. Richard A. Newcombe
  6. Geoffrey E. Hinton
  7. Alex Krizhevsky
  8. Philipp Krahenbuhl
  9. Pedro H. O. Pinheiro
  10. Piotr Doll'ar

Who trusts Martin Rünz overall

  1. Michael Strecke
  2. Yu-Shiang Wong
  3. Emanuele Palazzolo
  4. Binbin Xu
  5. Berta Bescós
  6. Andrew J. Davison
  7. Jörg Stückler
  8. Antoni Rosinol
  9. Jens Behley
  10. Shuaifeng Zhi

Papers from Martin Rünz's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers