CNN-based and Transformer-based architectures have been used to create synthetic data but have been limited since they require some ordering on the set of objects to yield good, tangible results. We wanted to transform a codebase such that it could handle "houses" with curated arrangement and thus generate more realistic scenes.

Project Report

Spring 2022
Technical Area(s)
Machine Learning (ML)