Yulan Guo

Computer Vision and Pattern Recognition · 2013–2022

A researcher in the Science corpus: 9 papers; trusts 656 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 313 citations into it; #10,354 of 21,575 by trust here, #5,987 by citations
• Computational Mechanics — 176 citations into it; #9,822 of 10,001 by trust here, #1,272 by citations
• Aerospace Engineering — 175 citations into it; #2,238 of 6,421 by trust here, #877 by citations
• Geology — 143 citations into it
• Environmental Engineering — 72 citations into it
• 3D Vision & Pose — 53 citations into it
• Artificial Intelligence — 44 citations into it
• Computer Graphics and Computer-Aided Design — 24 citations into it

Whom Yulan Guo trusts overall

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

1. David G. Lowe
2. Yu Zhong
3. Geoffrey E. Hinton
4. Kaiming He
5. Alex Krizhevsky
6. Federico Tombari
7. Krystian Mikolajczyk
8. Ajmal Saeed Mian
9. Ross B. Girshick
10. Diederik P. Kingma

Who trusts Yulan Guo overall

1. Anastasia Ioannidou
2. Min Lu
3. Qian-Yi Zhou
4. Elisavet Chatzilari
5. Mohammed Bennamoun
6. Zan Gojcic
7. Heng Yang
8. Shi Qiu
9. S. Nikolopoulos
10. Sheng Ao

Papers from Yulan Guo's perspective

Ordered by how strongly the researchers Yulan Guo 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds (2019) — 2,046 citations
• 3D Object Recognition in Cluttered Scenes with Local Surface Features: A Survey (2014) — 606 citations
• A Comprehensive Performance Evaluation of 3D Local Feature Descriptors (2015) — 578 citations
• Rotational Projection Statistics for 3D Local Surface Description and Object Recognition (2013) — 668 citations
• Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds (2022) — 365 citations
• Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs (2020) — 376 citations
• SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration (2020) — 402 citations
• Deep Learning for 3D Point Clouds: A Survey (2019) — 2,282 citations
• Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features (2014) — 27 citations