Junyuan Xie

Computer Vision and Pattern Recognition · 2012–2019

A researcher in the Science corpus: 6 papers; trusts 570 researchers and is trusted by 891 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it; #1,488 of 21,575 by trust here, #1,545 by citations
• Artificial Intelligence — 71 citations into it; #4,569 of 35,345 by trust here, #4,577 by citations
• Model Architectures — 28 citations into it
• Optimization & Training — 22 citations into it
• Representation & Self-Supervised Learning — 18 citations into it; #622 of 3,145 by trust here, #877 by citations
• Graph Learning — 15 citations into it
• Media Technology — 12 citations into it
• Computational Mechanics — 9 citations into it

Whom Junyuan Xie trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Yann LeCun
5. Radford M. Neal
6. Ross B. Girshick
7. Kaiming He
8. Ilya Sutskever
9. Diederik P. Kingma
10. Ruslan Salakhutdinov

Who trusts Junyuan Xie overall

1. Kyunghyun Cho
2. Xifeng Guo
3. Andrea Vedaldi
4. Zhun Zhong
5. Yu Meng
6. Lovedeep Gondara
7. Elad Amrani
8. Yonghua Zhang
9. Simon Niklaus
10. Nantheera Anantrasirichai

Papers from Junyuan Xie's perspective

Ordered by how strongly the researchers Junyuan Xie 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Bag of Tricks for Image Classification with Convolutional Neural Networks (2018) — 1,617 citations
• Unsupervised Deep Embedding for Clustering Analysis (2015) — 3,503 citations
• Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks (2016) — 447 citations
• Image Denoising and Inpainting with Deep Neural Networks (2012) — 1,465 citations
• Bag of Freebies for Training Object Detection Neural Networks (2019) — 203 citations
• GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs (2018) — 641 citations