Zhanpeng Zhang

Computer Vision and Pattern Recognition · 2014–2019

A researcher in the Science corpus: 6 papers; trusts 828 researchers and is trusted by 803 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 177 citations into it; #1,539 of 21,575 by trust here, #2,316 by citations
• Artificial Intelligence — 68 citations into it
• Experimental and Cognitive Psychology — 27 citations into it
• Signal Processing — 27 citations into it; #744 of 7,572 by trust here, #538 by citations
• Representation & Self-Supervised Learning — 23 citations into it
• Model Architectures — 18 citations into it
• Natural Language Processing — 14 citations into it
• Evaluation & Benchmarks — 9 citations into it

Whom Zhanpeng Zhang trusts overall

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

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

Who trusts Zhanpeng Zhang overall

1. Hakan Bilen
2. Andrea Vedaldi
3. Ping Luo
4. James Thewlis
5. Xi Yin
6. Mingsheng Long
7. Yue Wu
8. Shan Li
9. Chen Change Loy
10. Xiaoming Liu

Papers from Zhanpeng Zhang's perspective

Ordered by how strongly the researchers Zhanpeng Zhang 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. 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. Long Short-Term Memory
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

• Facial Landmark Detection by Deep Multi-task Learning (2014) — 1,538 citations
• Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks (2016) — 5,675 citations
• Learning Deep Representation for Face Alignment with Auxiliary Attributes (2014) — 433 citations
• Learning Social Relation Traits from Face Images (2015) — 177 citations
• Multi-Modality Latent Interaction Network for Visual Question Answering (2019) — 87 citations
• From Facial Expression Recognition to Interpersonal Relation Prediction (2016) — 310 citations