Google Research

Computer Vision and Pattern Recognition

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 Google Research trusts overall

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

  1. Michael Niemeyer
  2. Vincent Sitzmann
  3. Nima Khademi Kalantari

Who trusts Google Research overall

  1. Heewoo Jun
  2. Zhipeng Cai
  3. Yiyi Liao

Papers from Google Research's perspective

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

  1. Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. ImageNet classification with deep convolutional neural networks
  7. GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
  8. Plenoxels: Radiance Fields without Neural Networks (Computer Vision and Pattern Recognition)
  9. Long Short-Term Memory
  10. ImageNet: A large-scale hierarchical image database

Their papers