Synthetic Data for Machine Learning

One Day Meeting: Synthetic Data for Machine Learning

Wednesday 8 November 2023

Chairs: Abdulrahman Kerim - UCA, Leandro Soriano Marcolino – Lancaster University, Erickson Nascimento - Universidade Federal de Minas Gerais & Microsoft

Keynote Speaker

Dr. Tadas Baltrusaitis (Principal Scientist, Microsoft)

Call for Papers

The recent success of Machine Learning (ML) models is associated with the ability to train deep models on large-scale training data. However, annotating large-scale datasets is still the bottleneck in Computer Vision (CV) and Natural Language Processing (NLP) fields. Furthermore, ensuring diverse training data under challenging attributes like adverse weather conditions or when data is scarce is not only dangerous, time-consuming, and hard to collect but also cumbersome and subjective to human errors in the annotation process. Synthetic data comes as a solution to help solve all the above issues. While its application in CV and NLP has attracted more attention, especially with the recent paradigm shift from model-centric ML to data-centric ML solutions. This Symposium explores all stages of synthetic data from its creation to use in training and as applications.

The Call for Papers can be found here.

Submission Deadline 5th July

We invite submissions from industry and academia, bringing together researchers and practitioners interested in all aspects of real data limitations, synthetic data-based solutions in the ML field, and their potential future applications.

Abstracts are not published, and the re-presentation of previous work is acceptable and encouraged.

Submit interest through:    Submit Interest here

Meeting Location

The meeting will take place at:

British Computer Society (BCS), 25 Copthall Avenue, London EC2R 7BP


We keep the cost of attending these events as low as possible to ensure no barriers from the whole computer vision community attending. The registration costs are as follows

Both Inc Lunch and refreshments for the day

Please register via charitysuite on this link:    Register Here