Qiuhong Ke

Computer Vision and Pattern Recognition · 2014–2021

A researcher in the Science corpus: 10 papers; trusts 1,740 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 556 citations into it; #5,658 of 21,575 by trust here, #5,711 by citations
• Artificial Intelligence — 287 citations into it; #10,170 of 35,345 by trust here, #10,319 by citations
• Biomedical Engineering — 172 citations into it; #2,921 of 10,734 by trust here, #3,650 by citations
• Human-Computer Interaction — 85 citations into it
• Model Architectures — 82 citations into it
• 3D Vision & Pose — 48 citations into it; #659 of 689 by trust here, #485 by citations
• Representation & Self-Supervised Learning — 46 citations into it
• Evaluation & Benchmarks — 39 citations into it

Whom Qiuhong Ke trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Karen Simonyan
5. Kaiming He
6. Ross B. Girshick
7. Yann LeCun
8. Andrew Zisserman
9. Ilya Sutskever
10. Alex Graves

Who trusts Qiuhong Ke overall

1. Jun Liu
2. Yifan Zhang
3. Zehua Sun
4. Mohammed Bennamoun
5. Lei Shi
6. Amir Shahroudy
7. Ke Cheng
8. G. Wang
9. Senjian An
10. Bingyi Zhang

Papers from Qiuhong Ke's perspective

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

Their papers

• A New Representation of Skeleton Sequences for 3D Action Recognition (2017) — 866 citations
• Learning Clip Representations for Skeleton-Based 3D Action Recognition (2018) — 258 citations
• Global Regularizer and Temporal-Aware Cross-Entropy for Skeleton-Based Early Action Recognition (2018) — 14 citations
• Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data (2021) — 47 citations
• Human Action Recognition From Various Data Modalities: A Review (2020) — 800 citations
• SkeletonNet: Mining Deep Part Features for 3-D Action Recognition (2017) — 158 citations
• Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction (2016) — 40 citations
• Spatial, Structural and Temporal Feature Learning for Human Interaction Prediction (2016) — 11 citations
• Human Interaction Prediction Using Deep Temporal Features (2016) — 44 citations
• Is Rotation a Nuisance in Shape Recognition? (2014) — 26 citations