Aliaksandr Siarohin

Computer Vision and Pattern Recognition · 2017–2024

A researcher in the Science corpus: 9 papers; trusts 1,087 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 335 citations into it; #7,586 of 21,575 by trust here, #4,834 by citations
• Artificial Intelligence — 141 citations into it; #33,221 of 35,345 by trust here, #21,878 by citations
• Generative Models — 112 citations into it; #1,156 of 1,956 by trust here, #1,054 by citations
• Representation & Self-Supervised Learning — 56 citations into it; #2,946 of 3,145 by trust here, #2,454 by citations
• Computer Graphics and Computer-Aided Design — 42 citations into it
• Computational Mechanics — 36 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Optimization & Training — 29 citations into it

Whom Aliaksandr Siarohin trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Karen Simonyan
8. Sergey Ioffe
9. Christian Szegedy
10. Andrew Zisserman

Who trusts Aliaksandr Siarohin overall

1. Jian Zhao
2. Aleksandr Ermolov
3. Yisroel Mirsky
4. Zhimeng Zhang
5. Adrien Bardes
6. Stéphane Lathuilière
7. Sergey Tulyakov
8. Nicu Sebe
9. Yin-Yin He
10. Jinbo Xing

Papers from Aliaksandr Siarohin's perspective

Ordered by how strongly the researchers Aliaksandr Siarohin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• First Order Motion Model for Image Animation (2020) — 1,235 citations
• Whitening for Self-Supervised Representation Learning (2020) — 400 citations
• Deformable GANs for Pose-Based Human Image Generation (2017) — 496 citations
• Motion Representations for Articulated Animation (2021) — 379 citations
• Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors (2023) — 475 citations
• Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers (2024) — 424 citations
• Whitening and Coloring transform for GANs (2018) — 12 citations
• Animating Arbitrary Objects via Deep Motion Transfer (2018) — 394 citations
• Whitening and Coloring Batch Transform for GANs (2018) — 56 citations