Jun Fu

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 786 researchers and is trusted by 80 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 148 citations into it; #3,519 of 21,575 by trust here, #2,754 by citations
• Artificial Intelligence — 64 citations into it; #22,249 of 35,345 by trust here, #17,412 by citations
• Model Architectures — 29 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Media Technology — 9 citations into it
• Aerospace Engineering — 5 citations into it
• Biophysics — 5 citations into it

Whom Jun Fu trusts overall

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

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

Who trusts Jun Fu overall

1. Yuhui Yuan
2. Liang-Chieh Chen
3. Junjun He
4. Meng-Hao Guo
5. Jingdong Wang
6. Hengshuang Zhao
7. Xiangtai Li
8. Yanwei Li
9. Robin Strudel
10. Zilong Huang

Papers from Jun Fu's perspective

Ordered by how strongly the researchers Jun Fu 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Dual Attention Network for Scene Segmentation (2018) — 6,139 citations
• Stacked Deconvolutional Network for Semantic Segmentation (2017) — 223 citations
• Scene Segmentation With Dual Relation-Aware Attention Network (2020) — 248 citations
• Adaptive Context Network for Scene Parsing (2019) — 149 citations