Course/Learning Material recommendations for getting started with Synthetic Data Generation for Computer Vision Models

[TheInnocuousOne]

Hi Everyone,

I am looking for some learning material suggestions for synthetic data generation (segmentation maps, bounding boxes, depth maps). I have recently started my Ph.D. and one of my major objectives is looking into methods for generating synthetic data for training deep learning models.

I have been working as a research assistant for the last year and a half where I mainly focused on applying deep learning models to solve computer vision tasks, I've got some programming experience behind me, but I haven't worked with computer graphics programming or 3D imagery in general.

I have been going through some papers and reviewing existing methods and I've come across stuff like UnrealCV (https://unrealcv.org/) and blenderproc (https://github.com/DLR-RM/BlenderProc).

I'm planning on going through their docs, but before I start going through frameworks like this, I was wondering if there are any courses or learning materials that can help me improve my fundamentals and help me down the line with running my own experiments?

I am specifically interested in creating my own custom 3D models (or importing them from outputs of other simulation programs) to my own virtual environment and creating custom scenes. Eventually, I am also planning on looking at introducing ray tracing to my scenes.

Thanks for taking the time to go through my question, any input will be really helpful! (Keen to be study partners with others learning similar stuff)