Weixia Zhang

Computer Vision and Pattern Recognition · 2019–2023

A researcher in the Science corpus: 3 papers; trusts 266 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 110 citations into it; #15,717 of 21,575 by trust here, #13,815 by citations
• Media Technology — 52 citations into it
• Artificial Intelligence — 41 citations into it
• Evaluation & Benchmarks — 23 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 9 citations into it

Whom Weixia Zhang trusts overall

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

1. Kede Ma
2. A. Bovik
3. Zhou Wang
4. Hamid R. Sheikh
5. Kaiming He
6. Geoffrey E. Hinton
7. Diederik P. Kingma
8. Sergey Ioffe
9. Deepti Ghadiyaram
10. Karen Simonyan

Who trusts Weixia Zhang overall

1. S. Alireza Golestaneh
2. Haoning Wu
3. Chaofeng Chen
4. Guangtao Zhai
5. Jianyi Wang
6. Kede Ma
7. Yuming Fang
8. Hancheng Zhu
9. Shaolin Su
10. Sidi Yang

Papers from Weixia Zhang's perspective

Ordered by how strongly the researchers Weixia 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
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

• Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network (2019) — 937 citations
• Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective (2023) — 409 citations
• Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild (2020) — 368 citations