New in 2.1 (Bastien Doignies, @cnrs.fr, LIRIS):

* 4 new samplers (from siggraph 2020, 2021, 2024 and 2025 papers)
* New metrics (semi-discrete Optimal Transport and Gaussian kernels)
* bugfixes..

Code: github.com/utk-team/utk
Release note: github.com/utk-team/utk...

Timelapse (beginning only)

We have also completely refactored the cmake scripts and the dependencies management: no more GMP, Boost::Integer instead, no more Qt, deps fetched using cmake/CPM...

and a brand new paraview (paraview.org) plugin to use DGtal features in paraview pipelines!

This version also contains many new features (see github.com/DGtal-team/D...). Among them, new corrected normal current differential estimators and volumetric tools (Voronoi maps and distance transformation) in the Shortcuts

Huge improvements on the python binding with many Shortcuts available 🐍(www.dgtal.org/doc/stable/m...)

This new version includes a brand new viewer that is based on polyscope (polyscope.run).

You can still use tricks. Eg fixing a max number of samples and optimising OT + progressivity for previous points, or use tile-based approaches projet.liris.cnrs.fr/polyhex/), or change the model/ energy (clamping in GBN or progressive Poisson disk), but you won’t get the same quality.

Oh I see… I missed the pointset vs sequence thing.
So yes having BN sequences could be hard depending on your mathematical BN model you consider. Top quality ones (GBN or OT based) rely on a global energy which may by incompatible with progressively generating samples.

www.geometry.caltech.edu/BlueNoise/ , abdallagafar.com/publications... or perso.liris.cnrs.fr/david.coeurj... ?
(more refs available in the related work sections)

I couldn’t agree more, definitely a future award-winning movie!

🤣 nope

Adding geogram 1.9.3 (github.com/BrunoLevy/ge...).

(Ping @brunolevy01.bsky.social)