1 code implementation • CVPR 2015 • Sergey Zagoruyko, Nikos Komodakis
In this paper we show how to learn directly from image data (i. e., without resorting to manually-designed features) a general similarity function for comparing image patches, which is a task of fundamental importance for many computer vision problems.
no code implementations • CVPR 2015 • Mateusz Kozinski, Raghudeep Gadde, Sergey Zagoruyko, Guillaume Obozinski, Renaud Marlet
We present a new shape prior formalism for segmentation of rectified facade images.
1 code implementation • 7 Apr 2016 • Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro O. Pinheiro, Sam Gross, Soumith Chintala, Piotr Dollár
To address these challenges, we test three modifications to the standard Fast R-CNN object detector: (1) skip connections that give the detector access to features at multiple network layers, (2) a foveal structure to exploit object context at multiple object resolutions, and (3) an integral loss function and corresponding network adjustment that improve localization.
Ranked #104 on Instance Segmentation on COCO test-dev
71 code implementations • 23 May 2016 • Sergey Zagoruyko, Nikos Komodakis
Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance.
Ranked #12 on Image Classification on SVHN
6 code implementations • 12 Dec 2016 • Sergey Zagoruyko, Nikos Komodakis
Attention plays a critical role in human visual experience.
Ranked #39 on Knowledge Distillation on ImageNet
2 code implementations • ICCV 2017 • Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko
Combining scattering networks with a modern ResNet, we achieve a single-crop top 5 error of 11. 4% on imagenet ILSVRC2012, comparable to the Resnet-18 architecture, while utilizing only 10 layers.
Ranked #73 on Image Classification on STL-10
3 code implementations • 1 Jun 2017 • Sergey Zagoruyko, Nikos Komodakis
Deep neural networks with skip-connections, such as ResNet, show excellent performance in various image classification benchmarks.
1 code implementation • 17 Sep 2018 • Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew Blaschko, Eugene Belilovsky
In particular, by working in scattering space, we achieve competitive results both for supervised and unsupervised learning tasks, while making progress towards constructing more interpretable CNNs.
1 code implementation • ECCV 2018 • Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko
We study the first-order scattering transform as a candidate for reducing the signal processed by a convolutional neural network (CNN).
1 code implementation • 28 Dec 2018 • Xu Shell Hu, Sergey Zagoruyko, Nikos Komodakis
We propose several ways to impose local symmetry in recurrent and convolutional neural networks, and show that our symmetry parameterizations satisfy universal approximation property for single hidden layer networks.
2 code implementations • 23 Apr 2019 • Yann Labbé, Sergey Zagoruyko, Igor Kalevatykh, Ivan Laptev, Justin Carpentier, Mathieu Aubry, Josef Sivic
We address the problem of visually guided rearrangement planning with many movable objects, i. e., finding a sequence of actions to move a set of objects from an initial arrangement to a desired one, while relying on visual inputs coming from an RGB camera.
no code implementations • 27 Jan 2020 • Tristan Cazenave, Yen-Chi Chen, Guan-Wei Chen, Shi-Yu Chen, Xian-Dong Chiu, Julien Dehos, Maria Elsa, Qucheng Gong, Hengyuan Hu, Vasil Khalidov, Cheng-Ling Li, Hsin-I Lin, Yu-Jin Lin, Xavier Martinet, Vegard Mella, Jeremy Rapin, Baptiste Roziere, Gabriel Synnaeve, Fabien Teytaud, Olivier Teytaud, Shi-Cheng Ye, Yi-Jun Ye, Shi-Jim Yen, Sergey Zagoruyko
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games.
37 code implementations • ECCV 2020 • Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko
We present a new method that views object detection as a direct set prediction problem.
Ranked #21 on Panoptic Segmentation on COCO minival
1 code implementation • 5 Oct 2022 • Eesha Kumar, Yiming Zhang, Stefano Pini, Simon Stent, Ana Ferreira, Sergey Zagoruyko, Christian S. Perone
The imitation learning of self-driving vehicle policies through behavioral cloning is often carried out in an open-loop fashion, ignoring the effect of actions to future states.
no code implementations • 3 Nov 2022 • Stefano Pini, Christian S. Perone, Aayush Ahuja, Ana Sofia Rufino Ferreira, Moritz Niendorf, Sergey Zagoruyko
The code for training and testing our model on a public prediction dataset and the video of the road test are available at https://woven. mobi/safepathnet
1 code implementation • CVPR 2023 • Ziqi Pang, Jie Li, Pavel Tokmakov, Dian Chen, Sergey Zagoruyko, Yu-Xiong Wang
It emphasizes spatio-temporal continuity and integrates both past and future reasoning for tracked objects.