Nadia Magnenat-Thalmann

Computer Vision and Pattern Recognition · 2013–2019

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nadia Magnenat-Thalmann trusts

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

  1. Yehuda Koren (in Information Systems)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Kaiming He (in Computer Vision and Pattern Recognition)
  4. Thomas Brox (in Computer Vision and Pattern Recognition)
  5. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  6. Jitendra Malik (in Computer Vision and Pattern Recognition)
  7. Jia Deng (in Computer Vision and Pattern Recognition)
  8. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  9. James J. Little (in Computer Vision and Pattern Recognition)
  10. Shaoqing Ren (in Computer Vision and Pattern Recognition)

Papers from Nadia Magnenat-Thalmann's perspective

Ordered by how strongly the researchers Nadia Magnenat-Thalmann 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. Stacked Hourglass Networks for Human Pose Estimation
  3. 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
  4. ImageNet classification with deep convolutional neural networks
  5. Non-local Neural Networks
  6. Convolutional Pose Machines
  7. Semi-Supervised Classification with Graph Convolutional Networks (International Conference on Learning Representations)
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Gradient-based learning applied to document recognition
  10. Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose

Their papers