Sergey Zagoruyko

Orcid: 0000-0001-9684-5240

According to our database1, Sergey Zagoruyko authored at least 22 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
A Computational Study of Matrix Decomposition Methods for Compression of Pre-trained Transformers.
Proceedings of the 37th Pacific Asia Conference on Language, 2023

Safe Real-World Autonomous Driving by Learning to Predict and Plan with a Mixture of Experts.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Transformers Compression: A Study of Matrix Decomposition Methods Using Fisher Information.
Proceedings of the Analysis of Images, Social Networks and Texts, 2023

2022
CW-ERM: Improving Autonomous Driving Planning with Closed-loop Weighted Empirical Risk Minimization.
CoRR, 2022

2020
Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning.
IEEE Robotics Autom. Lett., 2020

Polygames: Improved zero learning.
J. Int. Comput. Games Assoc., 2020

End-to-End Object Detection with Transformers.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Scattering Networks for Hybrid Representation Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Exploring weight symmetry in deep neural networks.
Comput. Vis. Image Underst., 2019

2018
Weight parameterizations in deep neural networks. (Paramétrisation des poids des réseaux de neurones profonds).
PhD thesis, 2018

Exploring Weight Symmetry in Deep Neural Network.
CoRR, 2018

Compressing the Input for CNNs with the First-Order Scattering Transform.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Deep compare: A study on using convolutional neural networks to compare image patches.
Comput. Vis. Image Underst., 2017

DiracNets: Training Very Deep Neural Networks Without Skip-Connections.
CoRR, 2017

Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer.
Proceedings of the 5th International Conference on Learning Representations, 2017

Scaling the Scattering Transform: Deep Hybrid Networks.
Proceedings of the IEEE International Conference on Computer Vision, 2017

2016
Depth Camera Based on Color-Coded Aperture.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

A MultiPath Network for Object Detection.
Proceedings of the British Machine Vision Conference 2016, 2016

Wide Residual Networks.
Proceedings of the British Machine Vision Conference 2016, 2016

2015
Learning to compare image patches via convolutional neural networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

A MRF shape prior for facade parsing with occlusions.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015


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