Artsiom Sanakoyeu

Computer Vision and Pattern Recognition · 2016–2024

A researcher in the Science corpus: 5 papers; trusts 737 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 100 citations into it; #8,081 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 43 citations into it; #12,311 of 35,345 by trust here, #16,166 by citations
• Representation & Self-Supervised Learning — 27 citations into it; #2,171 of 3,145 by trust here, #2,957 by citations
• Generative Models — 15 citations into it
• Optimization & Training — 14 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Computer Graphics and Computer-Aided Design — 8 citations into it
• Model Architectures — 8 citations into it

Whom Artsiom Sanakoyeu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. Ross B. Girshick
6. Karen Simonyan
7. Yoshua Bengio
8. Ilya Sutskever
9. Nitish Srivastava
10. Andrew Zisserman

Who trusts Artsiom Sanakoyeu overall

1. Xu Ji
2. Unaiza Ahsan
3. Nicholas I. Kolkin
4. Ahmet Iscen
5. Andrea Vedaldi
6. Yassine Ouali
7. Björn Ommer
8. Patrick Esser
9. Rishi Madhok
10. Adrien Bardes

Papers from Artsiom Sanakoyeu's perspective

Ordered by how strongly the researchers Artsiom Sanakoyeu 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. Gradient-based learning applied to document recognition
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. Going deeper with convolutions

Their papers

• CliqueCNN: Deep Unsupervised Exemplar Learning (2016) — 116 citations
• Deep Unsupervised Similarity Learning Using Partially Ordered Sets (2017) — 28 citations
• A Style-Aware Content Loss for Real-time HD Style Transfer (2018) — 230 citations
• Movie Gen: A Cast of Media Foundation Models (2024) — 592 citations
• Semi-Supervised Segmentation of Salt Bodies in Seismic Images using an Ensemble of Convolutional Neural Networks (2019) — 66 citations