Thomas Schöps

Computer Vision and Pattern Recognition · 2014–2019

A researcher in the Science corpus: 3 papers; trusts 199 researchers and is trusted by 364 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Schöps trusts overall

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

  1. Andreas Geiger
  2. Jakob J. Engel
  3. Jürgen Sturm
  4. Daniel Cremers
  5. Daniel Scharstein
  6. Heiko Hirschmüller
  7. Richard A. Newcombe
  8. Christian Kerl
  9. Thomas Whelan
  10. Matthias Nießner

Who trusts Thomas Schöps overall

  1. Zachary Teed
  2. Nan Yang
  3. Jia Deng
  4. Rui Wang
  5. Wei Yin
  6. Daniel Cremers
  7. Michael Bloesch
  8. Jakob J. Engel
  9. Torsten Sattler
  10. Andrew J. Davison

Papers from Thomas Schöps's perspective

Ordered by how strongly the researchers Thomas Schöps 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. 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. ImageNet Large Scale Visual Recognition Challenge
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Long Short-Term Memory
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers