most citedAn Overview of Deep Semi-Supervised Learning

244 citations · 246 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Spatial Contrastive Learning for Few-Shot Classification

Yassine Ouali, Céline Hudelot, Myriam Tami

In this paper, we explore contrastive learning for few-shot classification, in which we propose to use it as an additional auxiliary training objective acting as a data-dependent r…

cs.CV2020

Autoregressive Unsupervised Image Segmentation

Yassine Ouali, Céline Hudelot, Myriam Tami

In this work, we propose a new unsupervised image segmentation approach based on mutual information maximization between different constructed views of the inputs. Taking inspirati…

cs.LG2020244 cited

An Overview of Deep Semi-Supervised Learning

Yassine Ouali, Céline Hudelot, Myriam Tami

Deep neural networks demonstrated their ability to provide remarkable performances on a wide range of supervised learning tasks (e.g., image classification) when trained on extensi…

cs.LG20202 cited

Target Consistency for Domain Adaptation: when Robustness meets Transferability

Yassine Ouali, Victor Bouvier, Myriam Tami +1

Learning Invariant Representations has been successfully applied for reconciling a source and a target domain for Unsupervised Domain Adaptation. By investigating the robustness of…

cs.CV2020

Semi-Supervised Semantic Segmentation with Cross-Consistency Training

Yassine Ouali, Céline Hudelot, Myriam Tami

In this paper, we present a novel cross-consistency based semi-supervised approach for semantic segmentation. Consistency training has proven to be a powerful semi-supervised learn…