Xinjing Cheng

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 4 papers; trusts 892 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 164 citations into it; #9,281 of 21,575 by trust here, #4,865 by citations
• Aerospace Engineering — 40 citations into it
• Media Technology — 31 citations into it; #2,067 of 3,621 by trust here, #1,206 by citations
• Artificial Intelligence — 26 citations into it
• Evaluation & Benchmarks — 24 citations into it; #2,981 of 3,147 by trust here, #1,653 by citations
• Model Architectures — 19 citations into it
• 3D Vision & Pose — 16 citations into it
• Computational Mechanics — 12 citations into it

Whom Xinjing Cheng trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Karen Simonyan
6. Ross B. Girshick
7. Yann LeCun
8. Jia Deng
9. Rob Fergus
10. Andrew Zisserman

Who trusts Xinjing Cheng overall

1. Nantheera Anantrasirichai
2. Jamie Watson
3. Hamid Laga
4. Fangchang Ma
5. Jie Tang
6. Barbara Roessle
7. Jinsun Park
8. Shivam Duggal
9. Mu Hu
10. Kyle Gao

Papers from Xinjing Cheng's perspective

Ordered by how strongly the researchers Xinjing Cheng 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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

• The ApolloScape Dataset for Autonomous Driving (2018) — 677 citations
• The ApolloScape Open Dataset for Autonomous Driving and Its Application (2018) — 673 citations
• Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network (2018) — 381 citations
• Learning Depth with Convolutional Spatial Propagation Network (2018) — 378 citations