Peixi Peng

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 2 papers; trusts 151 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it; #18,540 of 21,575 by trust here, #11,721 by citations
• Artificial Intelligence — 38 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Computational Mechanics — 7 citations into it
• Safety, Robustness & Interpretability — 6 citations into it
• Signal Processing — 6 citations into it
• Media Technology — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Peixi Peng trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Rui Zhao
7. Yann LeCun
8. Dan Hendrycks
9. Martin Hirzer
10. Ross B. Girshick

Who trusts Peixi Peng overall

1. Liang Zheng
2. Zhun Zhong
3. Ancong Wu
4. Jingya Wang
5. Hong-Xing Yu
6. Weishi Zheng
7. Yutian Lin
8. Yi Yang
9. Yang Fu
10. Weijian Deng

Papers from Peixi Peng's perspective

Ordered by how strongly the researchers Peixi Peng 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Unsupervised Cross-Dataset Transfer Learning for Person Re-identification (2016) — 388 citations
• Adversarial Reciprocal Points Learning for Open Set Recognition (2021) — 466 citations