199 citations · 276 across the 3 of their papers we have counts for
5 papers
Boosting Few-Shot Visual Learning with Self-Supervision
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis +2
Few-shot learning and self-supervised learning address different facets of the same problem: how to train a model with little or no labeled data. Few-shot learning aims for optimiz…
Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learning
Spyros Gidaris, Nikos Komodakis
Given an initial recognition model already trained on a set of base classes, the goal of this work is to develop a meta-model for few-shot learning. The meta-model, given as input…
DiracNets: Training Very Deep Neural Networks Without Skip-Connections
Sergey Zagoruyko, Nikos Komodakis
Deep neural networks with skip-connections, such as ResNet, show excellent performance in various image classification benchmarks. It is though observed that the initial motivation…
Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization
Spyros Gidaris, Nikos Komodakis
The problem of computing category agnostic bounding box proposals is utilized as a core component in many computer vision tasks and thus has lately attracted a lot of attention. In…
Learning to Compare Image Patches via Convolutional Neural Networks
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…