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20152020
most citedLearning to Compare Image Patches via Convolutional Neural Networks

199 citations · 278 across the 4 of their papers we have counts for

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10 papers · 1 filter

cs.CV2020

OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning

Spyros Gidaris, Andrei Bursuc, Gilles Puy +3

Learning image representations without human supervision is an important and active research field. Several recent approaches have successfully leveraged the idea of making such a…

cs.CV2020

Learning Representations by Predicting Bags of Visual Words

Spyros Gidaris, Andrei Bursuc, Nikos Komodakis +2

Self-supervised representation learning targets to learn convnet-based image representations from unlabeled data. Inspired by the success of NLP methods in this area, in this work…

cs.CV2019

QUEST: Quantized embedding space for transferring knowledge

Himalaya Jain, Spyros Gidaris, Nikos Komodakis +2

Knowledge distillation refers to the process of training a compact student network to achieve better accuracy by learning from a high capacity teacher network. Most of the existing…

cs.CV2019

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…

cs.CV20192 cited

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…

cs.CV2018

Dynamic Few-Shot Visual Learning without Forgetting

Spyros Gidaris, Nikos Komodakis

The human visual system has the remarkably ability to be able to effortlessly learn novel concepts from only a few examples. Mimicking the same behavior on machine learning vision…