Zhifei Zhang

Computer Vision and Pattern Recognition · 2017–2022

A researcher in the Science corpus: 5 papers; trusts 329 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 101 citations into it; #8,934 of 21,575 by trust here, #8,409 by citations
• Artificial Intelligence — 54 citations into it
• Generative Models — 45 citations into it; #848 of 1,956 by trust here, #1,134 by citations
• Safety, Robustness & Interpretability — 22 citations into it
• Media Technology — 18 citations into it
• Optimization & Training — 9 citations into it
• Model Architectures — 8 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Zhifei Zhang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. David G. Lowe
4. Diederik P. Kingma
5. Karen Simonyan
6. Alex Krizhevsky
7. Yann LeCun
8. Yoshua Bengio
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Zhifei Zhang overall

1. Kimmo Kärkkäinen
2. Jungseock Joo
3. Eugene Bagdasarian
4. Zachary Bessinger
5. Yuval Alaluf
6. Fredrik K. Gustafsson
7. Ayush Jaiswal
8. Michele Merler
9. Yuji Roh
10. Felix J. S. Bragman

Papers from Zhifei Zhang's perspective

Ordered by how strongly the researchers Zhifei 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. 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. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Age Progression/Regression by Conditional Adversarial Autoencoder (2017) — 1,319 citations
• SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model (2022) — 379 citations
• Image Super-Resolution by Neural Texture Transfer (2019) — 342 citations
• Feature Importance-aware Transferable Adversarial Attacks (2021) — 329 citations
• Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning (2018) — 921 citations