Learning Module Improvements

Improvements we would like to add to the learning modules.

We have a guide on customizing learning modules here.

These are the things we would like to implement:

• Use off-object observations #numsteps #multiobj
• Reinitialize hypotheses when starting to recognize a new object #multiobj
• Improve bounded evidence performance #multiobj
• Use models with fewer points #speed #generalization
• Make it possible to store multiple feature maps on one graph #featsandmorph
• Test particle-filter-like resampling of hypothesis space #accuracy #speed
• Re-anchor hypotheses for robustness to noise and distortions #deformations #noise #generalization
• Less dependency on first observation #noise #multiobj
• Deal with incomplete models #learning
• Implement & test GNNs to model object behaviors & states #dynamic
• Deal with moving objects #dynamic #realworld
• Support scale invariance #scale
• Improve handling of symmetry #pose
• Use Better Priors for Hypothesis Initialization #numsteps #pose #scale

Please see the instructions here if you would like to tackle one of these tasks.