Yantao Shen

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 296 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #18,912 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 32 citations into it; #31,071 of 35,345 by trust here, #24,417 by citations
• Representation & Self-Supervised Learning — 15 citations into it
• Signal Processing — 11 citations into it
• Model Architectures — 9 citations into it
• Natural Language Processing — 5 citations into it

Whom Yantao Shen 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. Alex Graves
7. Yann LeCun
8. Christian Szegedy
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Yantao Shen overall

1. Mateusz Budnik
2. Federico Pernici
3. Qiang Meng
4. Alessandro Achille
5. Zhenyu Cui
6. Pirazh Khorramshahi
7. Yannis Avrithis
8. Matteo Bruni
9. Chixiang Zhang
10. Aditya Golatkar

Papers from Yantao Shen's perspective

Ordered by how strongly the researchers Yantao Shen 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Towards Backward-Compatible Representation Learning (2020) — 100 citations
• Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-Temporal Path Proposals (2017) — 300 citations