Due to the difficulty of collecting exhaustive multi-label annotations, multi-label datasets
often contain partial labels. We consider an extreme of this weakly supervised learning …

Labeled datasets are essential for supervised machine learning. Various data labeling tools
have been built to collect labels in different usage scenarios. However, developing labeling …

At present, in the age of computers and automation of services, deep learning (DL)
technology, mainly the subset of machine learning (ML) and artificial intelligence (AI), is …

Face recognition has become popular in the last few decades among researchers across
the globe due to its applicability in several domains. This problem becomes more …

In this paper, we discover and annotate visual attributes for the COCO dataset. With the goal
of enabling deeper object understanding, we deliver the largest attribute dataset to date …

Building on recent prior work that combines Google Street View (GSV) and crowdsourcing to
remotely collect information on physical world accessibility, we present the first'smart'system …

We introduce Fluid Annotation, an intuitive human-machine collaboration interface for
annotating the class label and outline of every object and background region in an image …

Due to the non-linear but highly interpretable representations, decision tree (DT) models
have significantly attracted a lot of attention of researchers. However, it is difficult to …

We introduce a conceptual model for scalability designed for visualization research. With
this model, we systematically analyze over 120 visualization publications from 1990 to 2020 …

Microtask crowdsourcing has enabled dataset advances in social science and machine
learning, but existing crowdsourcing schemes are too expensive to scale up with the …