S Kim, G Lee, S Bae, SY Yun - arXiv preprint arXiv:2010.06300, 2020 - researchgate.net
… To validate the efficacy of MixCo, it is applied to recent popular representationlearning … extended the concept of contrastive loss for visualrepresentationlearning to semi-positive …
… Our objective is to learnvisualrepresentation from multimodal data in a unified training framework. … We aim to learn high-quality visual features, which benefit from not only the additional …
A Diba, V Sharma, R Safdari, D Lotfi… - Proceedings of the …, 2021 - openaccess.thecvf.com
… -supervised visualrepresentationlearning method … contrastivelearning of representation (Vi2CLR) pipeline using clustering and instance discrimination objective in a contrastivelearn…
… Current self-supervised contrastivelearning methods assume implicit knowledge of … to learnvisualrepresentations which capture individual factors of variation in a contrastivelearning …
… representationlearning techniques have largely closed the gap between supervised and unsupervised learning … direction, we study contrastive selfsupervised learning on four diverse …
C Yang, Z An, L Cai, Y Xu - Proceedings of the AAAI Conference on …, 2022 - ojs.aaai.org
… learning method called Mutual ContrastiveLearning (MCL) for general visualrepresentation learning… The core idea of MCL is to perform mutual interaction and transfer of contrastive …
R Liu - arXiv preprint arXiv:2106.03259, 2021 - arxiv.org
… contrastivelearning method SimCLR [7] and in section 4.2 we introduce attempts to improve contrastive … Section 5.1 presents the model bias [44] in contrastivelearning, and is followed …
… that make representations from contrastivelearning more transferable … representations of contrastivelearning are much different than the cross-entropy model; in particular, contrastive …
… 48], connections are made of the contrastive loss to … propose a loss for supervised learning that builds on the contrastive self-… framework for contrastivelearning of visualrepresentations. …