H. Pfister

Computer Vision and Pattern Recognition · with Azem · 2020

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

Subfields

Whom H. Pfister trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)

Papers from H. Pfister's perspective

Ordered by how strongly the researchers H. Pfister 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. Fully convolutional networks for semantic segmentation
  3. Rethinking the Inception Architecture for Computer Vision
  4. Aggregated Residual Transformations for Deep Neural Networks
  5. Instance-Aware Semantic Segmentation via Multi-task Network Cascades
  6. Mask R-CNN
  7. Deep Learning
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet classification with deep convolutional neural networks
  10. Gradient-based learning applied to document recognition

Their papers