Xin Zhao

Computer Vision and Pattern Recognition · with Huang · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 980 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 156 citations into it; #4,633 of 21,575 by trust here, #6,606 by citations
• Artificial Intelligence — 36 citations into it; #30,413 of 35,345 by trust here, #18,586 by citations
• Aerospace Engineering — 12 citations into it
• Global and Planetary Change — 8 citations into it
• Media Technology — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Electrical and Electronic Engineering — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Xin Zhao 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. Piotr Doll'ar
6. Yann LeCun
7. Yoshua Bengio
8. Diederik P. Kingma
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Xin Zhao overall

1. Martin Danelljan
2. Ruoxi Deng
3. Xin Chen
4. Goutam Bhat
5. Mengyang Pu
6. Houwen Peng
7. Zhipeng Zhang
8. Bin Yan
9. Senthil Purushwalkam
10. Luc Van Gool

Papers from Xin Zhao's perspective

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

Their papers

• GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild (2018) — 1,831 citations
• SSAP: Single-Shot Instance Segmentation With Affinity Pyramid (2019) — 248 citations
• Deep Crisp Boundaries (2017) — 134 citations