Nikita Dvornik

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 738 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it; #6,791 of 21,575 by trust here, #8,122 by citations
• Artificial Intelligence — 41 citations into it; #21,920 of 35,345 by trust here, #22,463 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Media Technology — 5 citations into it

Whom Nikita Dvornik trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Shaoqing Ren
7. Yann LeCun
8. Tsung-Yi Lin
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Nikita Dvornik overall

1. Daniel Bolya
2. Lin Wang
3. Prateek Katiyar
4. Cordelia Schmid
5. Nanqing Dong
6. Tonmoy Saikia
7. Kevis-Kokitsi Maninis
8. Jiale Cao
9. Songtao Liu
10. Tao Lin

Papers from Nikita Dvornik's perspective

Ordered by how strongly the researchers Nikita Dvornik 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• BlitzNet: A Real-Time Deep Network for Scene Understanding (2017) — 211 citations
• Diversity With Cooperation: Ensemble Methods for Few-Shot Classification (2019) — 210 citations
• Modeling Visual Context is Key to Augmenting Object Detection Datasets (2018) — 279 citations