15 datasets found

Recommender systems (RecSys) play a vital role in online platforms, offering users personalized suggestions amidst vast information. Graph contrastive learning aims to learn...

Contrastive learning is one of the most successful paradigms for self-supervised learning (SSL). In a principled way, it considers two augmented views of the same image as...

UMIC: An unreferenced metric for image captioning via contrastive learning

The dataset used in the paper is a collection of pairs of observations (xi, ˜xi) from two modalities, where xi ∈ Rd1 and ˜xi ∈ Rd2. The dataset is used to evaluate the...

Adaptive Multi-head Contrastive Learning (AMCL) framework, which tackles intra- and inter-sample similarity and adaptive temperature mechanism re-weighting each similarity pair.

Contrastive learning for compact single image dehazing

Contrastive Analysis (CA) deals with the discovery of what is common and what is distinctive of a target domain compared to a background one.

Contrastive multiview coding.

Prototypical contrastive learning of unsupervised representations.

A simple framework for contrastive learning of visual representations.

Contrastive self-supervised learning (CSL) with a prototypical regularization has been introduced in learning meaningful representations for downstream tasks that require strong...

A simple method that minimizes computational resource footprint for CLIP (Contrastive Language Image Pretraining).

A simple framework for contrastive learning of visual representations.

The CLIP dataset is used to train a contrastive learning model.

Contrastive learning of person-independent representations for facial action unit detection