Dmitry Ulyanov

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 9 papers; trusts 958 researchers and is trusted by 3,349 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 162 citations into it; #620 of 21,575 by trust here, #1,065 by citations
• Generative Models — 97 citations into it; #190 of 1,956 by trust here, #271 by citations
• Artificial Intelligence — 47 citations into it; #1,588 of 35,345 by trust here, #2,853 by citations
• Media Technology — 34 citations into it
• Signal Processing — 26 citations into it
• Computer Graphics and Computer-Aided Design — 19 citations into it; #117 of 1,584 by trust here, #155 by citations
• Optimization & Training — 16 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Dmitry Ulyanov trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yoshua Bengio
6. Alex Krizhevsky
7. Jimmy Ba
8. Yann LeCun
9. Ian J. Goodfellow
10. Alec Radford

Who trusts Dmitry Ulyanov overall

1. Jun-Yan Zhu
2. Andrea Vedaldi
3. Yijun Li
4. Xun Huang
5. Yoshua Bengio
6. Ping Luo
7. Alexei A. Efros
8. Yongcheng Jing
9. Lior Wolf
10. Richard Zhang

Papers from Dmitry Ulyanov's perspective

Ordered by how strongly the researchers Dmitry Ulyanov 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. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
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

• Instance Normalization: The Missing Ingredient for Fast Stylization (2016) — 4,163 citations
• Deep Image Prior (2017) — 3,852 citations
• Texture Networks: Feed-forward Synthesis of Textures and Stylized Images (2016) — 1,012 citations
• Improved Texture Networks: Maximizing Quality and Diversity in Feed-Forward Stylization and Texture Synthesis (2017) — 866 citations
• It Takes (Only) Two: Adversarial Generator-Encoder Networks (2017) — 141 citations
• Image Manipulation with Perceptual Discriminators (2018) — 24 citations
• Neural Point-Based Graphics (2019) — 496 citations
• Adversarial Generator-Encoder Networks (2017) — 39 citations
• Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification (2015) — 376 citations