Xiao Chu

Computer Vision and Pattern Recognition · 2014–2021

A researcher in the Science corpus: 7 papers; trusts 1,166 researchers and is trusted by 252 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 256 citations into it; #2,439 of 21,575 by trust here, #3,267 by citations
• Artificial Intelligence — 118 citations into it; #19,759 of 35,345 by trust here, #10,065 by citations
• Model Architectures — 42 citations into it
• Human-Computer Interaction — 31 citations into it; #230 of 2,253 by trust here, #185 by citations
• Biomedical Engineering — 24 citations into it; #1,913 of 10,734 by trust here, #4,052 by citations
• Evaluation & Benchmarks — 19 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• 3D Vision & Pose — 10 citations into it

Whom Xiao Chu trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Yi Yang
6. Navneet Dalal
7. Yoshua Bengio
8. Yann LeCun
9. Deva Ramanan
10. Christian Szegedy

Who trusts Xiao Chu overall

1. Wanli Ouyang
2. Xiaogang Wang
3. Bin Xiao
4. Ke Sun
5. Xiao Sun
6. Mingsheng Long
7. Hongsheng Li
8. Wei Yang
9. Zhe Cao
10. Yu Zhang

Papers from Xiao Chu's perspective

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

Their papers

• Multi-context Attention for Human Pose Estimation (2017) — 689 citations
• Multi-source Deep Learning for Human Pose Estimation (2014) — 265 citations
• Structured Feature Learning for Pose Estimation (2016) — 269 citations
• Visual Question Generation as Dual Task of Visual Question Answering (2017) — 177 citations
• Multi-task Recurrent Neural Network for Immediacy Prediction (2015) — 54 citations
• CRF-CNN: Modeling Structured Information in Human Pose Estimation (2016) — 81 citations
• CBNet: A Composite Backbone Network Architecture for Object Detection (2021) — 224 citations