Hong-Xing Yu

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 602 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 200 citations into it; #6,871 of 21,575 by trust here, #6,606 by citations
• Computer Graphics and Computer-Aided Design — 50 citations into it
• 3D Vision & Pose — 45 citations into it
• Computational Mechanics — 40 citations into it
• Aerospace Engineering — 35 citations into it
• Generative Models — 34 citations into it; #1,594 of 1,956 by trust here, #1,926 by citations
• Artificial Intelligence — 22 citations into it
• Representation & Self-Supervised Learning — 14 citations into it; #1,476 of 3,145 by trust here, #2,263 by citations

Whom Hong-Xing Yu trusts overall

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

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

Who trusts Hong-Xing Yu overall

1. Mang Ye
2. Zhun Zhong
3. Liang Zheng
4. Guile Wu
5. Mateusz Budnik
6. Ancong Wu
7. Lingxiao He
8. Shaogang Gong
9. Jiawei Liu
10. Yixiao Ge

Papers from Hong-Xing Yu's perspective

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

Their papers

• Neural Radiance Flow for 4D View Synthesis and Video Processing (2020) — 345 citations
• Cross-View Asymmetric Metric Learning for Unsupervised Person Re-Identification (2017) — 341 citations
• OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets (2020) — 113 citations
• RGB-Infrared Cross-Modality Person Re-identification (2017) — 796 citations
• MIXGAN: Learning Concepts from Different Domains for Mixture Generation (2018) — 13 citations
• OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets (2020) — 47 citations