Jianqiang Huang

Computer Vision and Pattern Recognition · with Zhang · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 740 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 152 citations into it; #8,158 of 21,575 by trust here, #8,502 by citations
• Artificial Intelligence — 115 citations into it; #15,744 of 35,345 by trust here, #11,921 by citations
• Multimodal Learning — 49 citations into it; #1,127 of 1,211 by trust here, #1,004 by citations
• Natural Language Processing — 28 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Causal Inference & Discovery — 21 citations into it; #221 of 364 by trust here, #167 by citations
• Model Architectures — 18 citations into it
• Optimization & Training — 17 citations into it

Whom Jianqiang Huang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Alex Krizhevsky
5. Yoshua Bengio
6. Judea Pearl
7. Diederik P. Kingma
8. Shaoqing Ren
9. Ilya Sutskever
10. Yann LeCun

Who trusts Jianqiang Huang overall

1. Xinting Hu
2. Hanwang Zhang
3. Kaihua Tang
4. Dong Zhang
5. Aman Chadha
6. Xiansheng Hua
7. Xu Yang
8. Feihong Shen
9. Chunyan Miao
10. Yifan Zhang

Papers from Jianqiang Huang's perspective

Ordered by how strongly the researchers Jianqiang 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• Unbiased Scene Graph Generation From Biased Training (2020) — 853 citations
• Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect (2020) — 525 citations
• Visual Commonsense R-CNN (2020) — 296 citations
• Two Causal Principles for Improving Visual Dialog (2019) — 163 citations