Kun Wang

Computer Vision and Pattern Recognition · with Wang · 2017–2020

A researcher in the Science corpus: 5 papers; trusts 842 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 192 citations into it; #13,103 of 21,575 by trust here, #7,340 by citations
• Artificial Intelligence — 88 citations into it
• Model Architectures — 20 citations into it
• Aerospace Engineering — 16 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Multimodal Learning — 13 citations into it
• Media Technology — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Kun Wang trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Karen Simonyan
6. Pedro F. Felzenszwalb
7. Christian Szegedy
8. Shaoqing Ren
9. Andrew Zisserman
10. Yann LeCun

Who trusts Kun Wang overall

1. Zhaowei Cai
2. Wanli Ouyang
3. Zhengxia Zou
4. Jiangmiao Pang
5. Yikang Li

Papers from Kun Wang's perspective

Ordered by how strongly the researchers Kun Wang 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. 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

• Scene Graph Generation from Objects, Phrases and Region Captions (2017) — 551 citations
• Chained Cascade Network for Object Detection (2017) — 56 citations
• Adapting Object Detectors with Conditional Domain Normalization (2020) — 100 citations
• Learning Chained Deep Features and Classifiers for Cascade in Object Detection (2017) — 20 citations
• DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks (2017) — 134 citations