Xiangxin Zhu

Computer Vision and Pattern Recognition · 2007–2014

A researcher in the Science corpus: 4 papers; trusts 286 researchers and is trusted by 2,638 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it; #743 of 21,575 by trust here, #3,017 by citations
• Artificial Intelligence — 14 citations into it; #13,371 of 35,345 by trust here, #11,072 by citations
• Evaluation & Benchmarks — 7 citations into it; #2,793 of 3,147 by trust here, #2,095 by citations

Whom Xiangxin Zhu trusts overall

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

1. Pedro F. Felzenszwalb
2. Navneet Dalal
3. J. Platt
4. Deva Ramanan
5. Ross B. Girshick
6. Sergey Ioffe
7. Geoffrey E. Hinton
8. Andrew Zisserman
9. Antonio Torralba
10. Chih-Jen Lin

Who trusts Xiangxin Zhu overall

1. Junjie Yan
2. Tadas Baltrusaitis
3. Ping Luo
4. Zhen Lei
5. Deva Ramanan
6. Chen Change Loy
7. Christos Sagonas
8. Rajeev Ranjan
9. Ross B. Girshick
10. Shaoqing Ren

Papers from Xiangxin Zhu's perspective

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

Their papers

• Face detection, pose estimation, and landmark localization in the wild (2012) — 2,400 citations
• Do We Need More Training Data or Better Models for Object Detection? (2012) — 191 citations
• Capturing Long-Tail Distributions of Object Subcategories (2014) — 179 citations
• Learning Multi-scale Block Local Binary Patterns for Face Recognition (2007) — 678 citations