Introduction to the Special Issue on Realistic Synthetic Data: Generation, Learning, Evaluation

Abstract

This is the foreword of our special issue volume on Realistic Synthetic Data: Generation, Learning, Evaluation organized with the ACM Transactions on Multimedia Computing, Communications, and Applications. It presents the target of the special issue that relates to synthetic data for various modalities, e.g., signals, images, volumes, audio, etc., controllable generation for learning from synthetic data, transfer learning and generalization of models, causality in data generation, addressing bias, limitations and trustworthiness in data generation, evaluation measures/protocols and benchmarks to assess quality of synthetic content, open synthetic datasets and software tools, and ethical aspects of synthetic data. The call for papers received a record number of 40 submissions out of which 15 were finally accepted for publication. This introduction provides an overview of the topics of each of the articles.