Mingyuan Zhang

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 5 papers; trusts 459 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 151 citations into it; #20,005 of 21,575 by trust here, #7,499 by citations
• Artificial Intelligence — 76 citations into it
• Model Architectures — 29 citations into it; #2,060 of 2,278 by trust here, #1,285 by citations
• Control and Systems Engineering — 27 citations into it
• Generative Models — 25 citations into it
• Large Language Models — 9 citations into it
• Media Technology — 9 citations into it

Whom Mingyuan Zhang trusts overall

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

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

Who trusts Mingyuan Zhang overall

1. Biao Jiang
2. Xin Chen
3. Shuhao Cao
4. Chuan Guo
5. Jo-Han Tseng
6. Yonatan Shafir
7. Ye Yuan
8. Markus Norman Rabe
9. Huiyu Wang
10. Jianrong Zhang

Papers from Mingyuan Zhang's perspective

Ordered by how strongly the researchers Mingyuan Zhang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Efficient Attention: Attention with Linear Complexities (2018) — 772 citations
• MotionDiffuse: Text-Driven Human Motion Generation With Diffusion Model (2022) — 1,020 citations
• Delving Deep into the Generalization of Vision Transformers under Distribution Shifts (2021) — 138 citations
• ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model (2023) — 333 citations
• Factorized Attention: Self-Attention with Linear Complexities (2018) — 13 citations