We've been building deep learning vision models in simulation, without any real labeled data... and it's working!
Have you recently worked on a vision model for which data was very difficult to source?
* Could be a rare event that happens once a week?
* Could be too difficult to get precise labels? (6D-pose, cuboids)
* Could be a budget & speed of iteration issue..
Really looking to broaden our understanding of applications beyond robotics & manufacturing.
Here is a recent example from our test bench (30 sec): https://youtu.be/D33acz5mI10
* Mask R-CNN trained on 10,000 samples from SBX Quicksynth with 3D scans from YCB Benchmarks, running on RealSense SR305 RGB channel.
* 3D scans from: https://ycbbenchmarks.com/
* Data from: https://sbxrobotics.com, built on UE4