Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Neural Information Processing Systems: Crowdsourcing and Machine Learning Workshop
We are interested in improving the quality and coverage of a knowledge graph through crowdsourcing features built into a social networking service. In this setting, most participants are casual users, making only a few contributions, and do so incidentally in the course of using the service. Techniques that make assumptions about the matching of users to questions, or the number of answers per user or per question do not work well under such circumstances.
We present an approach to model user trust when prior history is lacking, so that we can incorporate more new users’ contributions into crowdsourced decisions, and provide quicker feedback to new participants. Specifically, we present a logistic regression classifier for first-time contributions, and study the effect of prior knowledge about user demographics on this classifier using Facebook crowdsourcing datasets.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
Ilkan Esiyok, Pascal Berrang, Katriel Cohn-Gordon, Robert Künnemann