Matthias Muller

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Matthias Muller trusts

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

  1. Rob Fergus (in Computer Vision and Pattern Recognition)
  2. Vladlen Koltun (in Computer Vision and Pattern Recognition)
  3. Andreas Geiger (in Computer Vision and Pattern Recognition)
  4. Kaiming He (in Computer Vision and Pattern Recognition)
  5. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  6. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  7. Jitendra Malik (in Computer Vision and Pattern Recognition)
  8. Derek Hoiem (in Computer Vision and Pattern Recognition)
  9. Noah Snavely (in Computer Vision and Pattern Recognition)
  10. Alex Krizhevsky (in Computer Vision and Pattern Recognition)

Papers from Matthias Muller's perspective

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

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

Their papers