Jian Sun

Computer Vision and Pattern Recognition · IEEE Transactions on Image Processing · 2008–2021

A researcher in the Science corpus: 9 papers; trusts 855 researchers and is trusted by 478 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 208 citations into it; #1,924 of 21,575 by trust here, #3,538 by citations
• Artificial Intelligence — 57 citations into it; #8,946 of 35,345 by trust here, #13,760 by citations
• Media Technology — 51 citations into it; #273 of 3,621 by trust here, #353 by citations
• Computational Mechanics — 47 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Signal Processing — 17 citations into it
• Radiology, Nuclear Medicine and Imaging — 15 citations into it
• Optimization & Training — 13 citations into it

Whom Jian Sun trusts overall

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

1. William T. Freeman
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Yann LeCun
5. Kaiming He
6. Yoshua Bengio
7. Diederik P. Kingma
8. Ilya Sutskever
9. Andrew Zisserman
10. Ross B. Girshick

Who trusts Jian Sun overall

1. Chih-Yuan Yang
2. Ming-Hsuan Yang
3. Kamal Nasrollahi
4. Chao Ma
5. Jia-Bin Huang
6. Jiwon Kim
7. Kaihao Zhang
8. Radu Timofte
9. Chao Dong
10. Gong Cheng

Papers from Jian Sun's perspective

Ordered by how strongly the researchers Jian Sun 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. 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. Going deeper with convolutions

Their papers

• Image super-resolution using gradient profile prior (2008) — 1,020 citations
• Learning Discriminative Part Detectors for Image Classification and Cosegmentation (2013) — 142 citations
• Learning a convolutional neural network for non-uniform motion blur removal (2015) — 920 citations
• Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement (2011) — 328 citations
• Learning to Estimate and Remove Non-uniform Image Blur (2013) — 106 citations
• Image Inpainting by Patch Propagation Using Patch Sparsity (2010) — 601 citations
• Training Networks in Null Space of Feature Covariance for Continual Learning (2021) — 225 citations
• Finding Matches in a Haystack: A Max-Pooling Strategy for Graph Matching in the Presence of Outliers (2014) — 128 citations
• ADMM-CSNet: A Deep Learning Approach for Image Compressive Sensing (2020) — 829 citations