Julia frameworks for large-scale nonlinear least-squares optimization for computer vision

I wrote two packages that together can do bundle adjustment (and other such optimizations) very efficiently:

NLLSsolver.jl - A non-linear least squares solver that supports sparse problems, auto-differentiation, and robustified costs.

VisualGeometryOptimization.jl - This package constructs visual geometry optimization problems that can then be solved by NLLSsolver.

I am seeking collaborators to further extend the functionality of the second package.

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