Chao Yang

Computer Vision and Pattern Recognition · with Huang · 2016–2018

A researcher in the Science corpus: 5 papers; trusts 746 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 155 citations into it; #6,929 of 21,575 by trust here, #4,067 by citations
• Generative Models — 83 citations into it; #873 of 1,956 by trust here, #533 by citations
• Artificial Intelligence — 32 citations into it
• Computer Graphics and Computer-Aided Design — 21 citations into it
• Evaluation & Benchmarks — 19 citations into it
• Media Technology — 16 citations into it
• Model Architectures — 15 citations into it
• Optimization & Training — 9 citations into it

Whom Chao Yang trusts overall

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

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

Who trusts Chao Yang overall

1. Hongyu Liu
2. Yanhong Zeng
3. Kamyar Nazeri
4. Manyu Zhu
5. Chuanxia Zheng
6. Roman Suvorov
7. Yi Wang
8. Bin Jiang
9. Jiahui Yu
10. Guilin Liu

Papers from Chao Yang's perspective

Ordered by how strongly the researchers Chao Yang 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. Long Short-Term Memory
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. Going deeper with convolutions

Their papers

• High-Resolution Image Inpainting Using Multi-scale Neural Patch Synthesis (2016) — 832 citations
• SPG-Net: Segmentation Prediction and Guidance Network for Image Inpainting (2018) — 197 citations
• Contextual-Based Image Inpainting: Infer, Match, and Translate (2017) — 227 citations
• Shape Inpainting Using 3D Generative Adversarial Network and Recurrent Convolutional Networks (2017) — 186 citations
• Image Inpainting using Block-wise Procedural Training with Annealed Adversarial Counterpart (2018) — 25 citations