This is a discuss and record for the summary about "Vehicle Pose Transform by GAN for Re-Id KeyPoint generator" problem. Now is working on the Sol.2., create another model to satisfy the GAN framework.
The structure of system framework is below:
- will input image
Input Image x
and a sequence with vehicle key-pointTarget pose
. Generator
generate fake image with target pose in specific key-point, target pose is come from real image.- Compute Loss between fake image and real image, real image includes the target pose.
- will input image
Input Image x
without vehicle key-pointTarget pose
. Generator
generate fake image in target pose with specific key-point.
In training, not all vehicle have all type of pose, so Generator
will lack some specific key-point.
we can not generate doesn't exist pose vehicle. The structure of training framework will become:
generator
will fail to generate fake image.
- Take the average of the KeyPoints for each pose of all types, and use the average instead if a vehicle of a certain type does not have KeyPoint on a specific pose.
- Create another model for generate vehicle KeyPoint.
- If vehicle doesn't have KeyPoint on a specific pose, then use CycleGAN-like algo. to generate fake image, Else using original GAN.