Open clusters are central elements of our understanding of the Galactic disc evolution, as an accurate determination of their parameters leads to an unbiased picture of our Galaxy's structure. Extending the analysis towards fainter magnitudes in cluster sequences has a significant impact on the derived fundamental parameters, such as extinction and total mass. We perform a homogeneous analysis of six open stellar clusters in the Galactic disc using kinematic and photometric information from the Gaia DR2 and VVV surveys: NGC6067, NGC6259, NGC4815, Pismis18, Trumpler23, and Trumpler20. We implement two coarse-to-fine characterization methods: first, we employ Gaussian mixture models to tag fields around each open cluster in the proper motion space, and then we apply an unsupervised machine learning method to make the membership assignment to each cluster. For the studied clusters, with ages in the similar to 120-1900Myr range, we report an increase of similar to 45 percent new member candidates on average in our sample. The data-driven selection approach of cluster members makes our catalogue a valuable resource for testing stellar evolutionary models and for assessing the cluster low-to-intermediate mass populations. This study is the first of a series intended to homogeneously reveal open cluster near-infrared sequences.