Title: Neuropostors: a Neural Rendering approach to Crowd Synthesis
Supervision Team: Carol O’Sullivan, TCD / Sam Redfern, UoG
In computer graphics, crowd synthesis is a challenging problem due to high computational and labour costs. In this project, we propose to harness new developments in the field of Neural Rendering (NR) and apply novel machine learning methods to this problem. Building on initial results, the student will a) implement a novel hybrid image/geometry crowd animation and rendering system (Neuropostors) that uses new NR methods to facilitate limitless variety with real-time performance; and b) conduct a thorough set of quantitative and qualitative experiments, including perceptual evaluations, to drive the development of, and evaluate, the system.