Virginia Estellers

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Virginia Estellers trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  3. X. Zhang (in Computer Vision and Pattern Recognition)
  4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  5. Ross B. Girshick (in Computer Vision and Pattern Recognition)

Papers from Virginia Estellers's perspective

Ordered by how strongly the researchers Virginia Estellers 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Et al
  4. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  5. ImageNet classification with deep convolutional neural networks
  6. A Morphable Model For The Synthesis Of 3D Faces
  7. Real-time human pose recognition in parts from single depth images
  8. Gradient-based learning applied to document recognition
  9. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers