Guolei Sun

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 6 papers; trusts 1,075 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 295 citations into it; #10,726 of 21,575 by trust here, #4,750 by citations
• Artificial Intelligence — 115 citations into it
• Model Architectures — 63 citations into it
• Media Technology — 52 citations into it; #2,613 of 3,621 by trust here, #703 by citations
• Evaluation & Benchmarks — 26 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Computational Mechanics — 9 citations into it
• Optimization & Training — 9 citations into it

Whom Guolei Sun trusts overall

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

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

Who trusts Guolei Sun overall

1. Peng-Tao Jiang
2. Seungho Lee
3. Deng-Ping Fan
4. Fabio Cermelli
5. Yuliang Zou
6. Amita Kamath
7. Yazhou Yao
8. Jingyun Liang
9. Yu-Huan Wu
10. Sijie Li

Papers from Guolei Sun's perspective

Ordered by how strongly the researchers Guolei Sun 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• SwinIR: Image Restoration Using Swin Transformer (2021) — 4,894 citations
• Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation (2020) — 356 citations
• Camouflaged Object Detection (2020) — 720 citations
• iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images (2019) — 507 citations
• Object Counting and Instance Segmentation With Image-Level Supervision (2019) — 133 citations
• Transformer in Convolutional Neural Networks (2021) — 71 citations