Fangyi Zhang

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 7 papers; trusts 224 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 138 citations into it; #9,131 of 21,575 by trust here, #5,116 by citations
• Artificial Intelligence — 54 citations into it; #22,278 of 35,345 by trust here, #14,718 by citations
• Control and Systems Engineering — 32 citations into it; #4,739 of 8,257 by trust here, #1,592 by citations
• Reinforcement Learning — 31 citations into it
• Evaluation & Benchmarks — 27 citations into it
• Aerospace Engineering — 24 citations into it; #3,258 of 6,421 by trust here, #1,134 by citations
• Biomedical Engineering — 13 citations into it
• Model Architectures — 11 citations into it

Whom Fangyi Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Andrew Zisserman
4. Karen Simonyan
5. Ilya Sutskever
6. Kaiming He
7. Vittorio Ferrari
8. Yoshua Bengio
9. Sergey Levine
10. Diederik P. Kingma

Who trusts Fangyi Zhang overall

1. Lei Tai
2. Yongming Rao
3. Andrew Hundt
4. Oliver Kroemer
5. Jonathan Tremblay
6. Eric Tzeng
7. Ji Lin
8. Christopher Xie
9. Jiwen Lu
10. Deirdre Quillen

Papers from Fangyi Zhang's perspective

Ordered by how strongly the researchers Fangyi Zhang 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
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

• SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks (2018) — 2,218 citations
• Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control (2015) — 289 citations
• Vision-Based Reaching Using Modular Deep Networks: from Simulation to the Real World (2016) — 18 citations
• The Seventh Visual Object Tracking VOT2019 Challenge Results (2019) — 486 citations
• Sim-to-real Transfer of Visuo-motor Policies for Reaching in Clutter: Domain Randomization and Adaptation with Modular Networks (2017) — 38 citations
• Modular Deep Q Networks for Sim-to-real Transfer of Visuo-motor Policies (2016) — 42 citations
• The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research (2016) — 83 citations