Jiangjiang Liu

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 5 papers; trusts 961 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 301 citations into it; #6,157 of 21,575 by trust here, #4,781 by citations
• Artificial Intelligence — 127 citations into it
• Model Architectures — 85 citations into it
• Cognitive Neuroscience — 36 citations into it; #3,316 of 10,852 by trust here, #3,051 by citations
• Sensory Systems — 16 citations into it
• Media Technology — 15 citations into it
• Optimization & Training — 15 citations into it

Whom Jiangjiang Liu trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Karen Simonyan
4. Ross B. Girshick
5. Geoffrey E. Hinton
6. Christian Szegedy
7. Diederik P. Kingma
8. Ilya Sutskever
9. Andrew Zisserman
10. Yoshua Bengio

Who trusts Jiangjiang Liu overall

1. Deng-Ping Fan
2. Junhang Wei
3. Qibin Hou
4. Ming-Ming Cheng
5. Ge-Peng Ji
6. Wenguan Wang
7. Fan Yang
8. Shuhui Wang
9. Guolei Sun
10. Ling Shao

Papers from Jiangjiang Liu's perspective

Ordered by how strongly the researchers Jiangjiang Liu 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. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground (2018) — 333 citations
• EGNet: Edge Guidance Network for Salient Object Detection (2019) — 1,078 citations
• Improving Convolutional Networks With Self-Calibrated Convolutions (2020) — 421 citations
• A Simple Pooling-Based Design for Real-Time Salient Object Detection (2019) — 991 citations
• Attention mechanisms in computer vision: A survey (2021) — 2,419 citations