Sergey Zakharov

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 4 papers; trusts 526 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 144 citations into it; #12,496 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 37 citations into it
• Aerospace Engineering — 31 citations into it; #3,266 of 6,421 by trust here, #3,764 by citations
• Computational Mechanics — 28 citations into it; #9,850 of 10,001 by trust here, #2,509 by citations
• Generative Models — 26 citations into it
• Computer Graphics and Computer-Aided Design — 25 citations into it; #1,546 of 1,584 by trust here, #526 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Control and Systems Engineering — 8 citations into it

Whom Sergey Zakharov 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. Stefan Hinterstoißer
6. Shaoqing Ren
7. Yann LeCun
8. Karen Simonyan
9. Yoshua Bengio
10. Diederik P. Kingma

Who trusts Sergey Zakharov overall

1. Yann Labb'e
2. Meng Tian
3. Shujun Wang
4. Yen-Chen Lin
5. Zicong Fan
6. Tomas Hodan
7. Sergey I. Nikolenko
8. Wadim Kehl
9. Marcelo H. Ang Jr.
10. Justin Carpentier

Papers from Sergey Zakharov's perspective

Ordered by how strongly the researchers Sergey Zakharov 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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

• Zero-1-to-3: Zero-shot One Image to 3D Object (2023) — 1,787 citations
• DPOD: 6D Pose Object Detector and Refiner (2019) — 498 citations
• DepthSynth: Real-Time Realistic Synthetic Data Generation from CAD Models for 2.5D Recognition (2017) — 73 citations
• DeceptionNet: Network-Driven Domain Randomization (2019) — 100 citations