Zelun Luo

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 5 papers; trusts 983 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 238 citations into it; #10,467 of 21,575 by trust here, #5,806 by citations
• Artificial Intelligence — 108 citations into it; #21,539 of 35,345 by trust here, #9,870 by citations
• Representation & Self-Supervised Learning — 46 citations into it; #2,737 of 3,145 by trust here, #2,330 by citations
• Biomedical Engineering — 29 citations into it
• Model Architectures — 29 citations into it
• Human-Computer Interaction — 22 citations into it
• Media Technology — 21 citations into it; #3,354 of 3,621 by trust here, #1,923 by citations
• Aerospace Engineering — 19 citations into it

Whom Zelun Luo trusts overall

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

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

Who trusts Zelun Luo overall

1. Hossein Rahmani
2. Vincent Le Guen
3. Yulai Cong
4. Jogendra Nath Kundu
5. Nuno C. Garcia
6. Miaoyun Zhao
7. Biagio Brattoli
8. Nawid Sayed
9. Uta Büchler
10. Xinyang Chen

Papers from Zelun Luo's perspective

Ordered by how strongly the researchers Zelun Luo 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. 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

• Label Efficient Learning of Transferable Representations acrosss Domains and Tasks (2017) — 290 citations
• DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency (2018) — 504 citations
• Unsupervised Learning of Long-Term Motion Dynamics for Videos (2017) — 196 citations
• Graph Distillation for Action Detection with Privileged Modalities (2017) — 118 citations
• Towards Viewpoint Invariant 3D Human Pose Estimation (2016) — 176 citations