Binbin Huang

Computer Vision and Pattern Recognition · with Chen · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Binbin Huang trusts overall

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

  1. Jonathan T. Barron
  2. Christian Reiser
  3. Peter Hedman
  4. Michael Oechsle
  5. Lars M. Mescheder
  6. Ben Mildenhall
  7. T. Muller
  8. Andreas Geiger
  9. Johannes L. Schönberger
  10. Michael Niemeyer

Who trusts Binbin Huang overall

  1. Zehao Yu
  2. Kerui Ren
  3. Torsten Sattler
  4. Lihan Jiang

Papers from Binbin Huang's perspective

Ordered by how strongly the researchers Binbin Huang 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. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. GENERATIVE ADVERSARIAL NETS
  8. Long Short-Term Memory
  9. Gradient-based learning applied to document recognition
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers