Shu Kong

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 5 papers; trusts 1,737 researchers and is trusted by 209 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 192 citations into it; #2,623 of 21,575 by trust here, #7,027 by citations
• Artificial Intelligence — 95 citations into it; #9,079 of 35,345 by trust here, #16,166 by citations
• Model Architectures — 24 citations into it
• Aerospace Engineering — 17 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Media Technology — 16 citations into it
• Efficiency & Compression — 12 citations into it

Whom Shu Kong trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Ross B. Girshick
6. Yann LeCun
7. Yoshua Bengio
8. Andrew Zisserman
9. David G. Lowe
10. Diederik P. Kingma

Who trusts Shu Kong overall

1. Rohit Girdhar
2. Charless C. Fowlkes
3. Hossein Gholamalinezhad
4. Lei Ke
5. Tan Yu
6. Wenguan Wang
7. David Novotný
8. Claudio Michaelis
9. Christopher Xie
10. Xing Wei

Papers from Shu Kong's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Low-Rank Bilinear Pooling for Fine-Grained Classification (2016) — 375 citations
• Recurrent Pixel Embedding for Instance Grouping (2017) — 188 citations
• Photo Aesthetics Ranking Network with Attributes and Content Adaptation (2016) — 538 citations
• OpenGAN: Open-Set Recognition via Open Data Generation (2021) — 297 citations
• Pixel-Wise Attentional Gating for Scene Parsing (2018) — 43 citations