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Code for Surface Winding Numbers is out! Input a triangle mesh & a curve on the mesh -> get the winding number function & decomposition of the curve into bounding + nonbounding components. Works with surfaces and curves of general topology. C++ code: github.com/nzfeng/SWN

Interested in animation? We've created artist tools that directly manipulate *contact areas between objects*, allowing intuitive modeling of contact-rich interactions & automatic pose optimization. Contact Arjun Lakshmipathy (andrew.cmu.edu/user/aslakshm/) for code!

Super proud and excited for my student Zoë Marschner, who is one of only 18 recipients of the Fannie and John Hertz Foundation PhD fellowship! 🥳🎉🪅 Zoë has already done some top-notch work in geometry processing, which you can check out here: zoemarschner.com

One of my all-time favorite paper titles is "You Can Find Geodesic Paths in Triangle Meshes by Just Flipping Edges" by Nick Sharp and Keenan Crane. The entire core method of the paper is described fully by just the title! We need more papers like this. nmwsharp.com/research/flip-…

#geogram/Graphite and Nick Sharp's Polyscope play well together with Python ! Two Symposium on Geometry Processing award-winning softwares at your fingertips ! (cc Nicolò Campolongo : you need to import polyscope *before* gompy)

Very proud of my group Geometry Collective, for their consistent focus on quality in research. We have 5 papers at #SIGGRAPH2024, including two Best Paper Awards and one Honorable Mention. Only 5 and 12 such awards (respectively) are given out total, from a pool of ~840 submissions

Also proud of my student Mark Gillespie, who won *yet another* Best Paper (Honorable Mention) for very cool work on solid 3D knitting: markjgillespie.com/Research/solid… Altogether, this means Carnegie Mellon University Computer Graphics is taking home about 25% of all #SIGGRAPH2024 paper awards…!

Heads up that if you’re at #SGP2024 this week, we’ve created a channel on the Geometry Processing Worldwide Discord for folks to chat and coordinate! Even if you’re not at SGP, there’s a lot of great geometry processing talk happening here: discord.gg/Y8NwgQfwM4

Pretty compelling evidence that spreading out SGP locations beyond Western Europe is good for the growth of our community:

For better or for worse, the Geometry Collective is now also on Threads as geometry.collective: threads.net/@geometry.coll…

The talk, slides, and code for our SGP graduate school course on MCGP can be found here: rohan-sawhney.github.io/mcgp-resources/ We cover a lot of ground: Monte Carlo integration, differential equations, Brownian motion, and of course walk on spheres, which nicely ties all these topics

A quick tutorial on polyscope in Python, in just a few tweets from Bruno Levy Bruno has been showing some great experiments this past week combining Polyscope with the excellent #geogram + Graphite, I love it!!

PSA: If you're making a poster for your #SIGGRAPH2024 talk, these are the dimensions (photo courtesy of Leona Caffey / ACM SIGGRAPH):

Need to solve PDEs, and struggle with meshing? Heard about "Walk on Spheres," but didn't know where to start? Check out the awesome intro course by Rohan Sawhney and @baileymmiller1, just posted from #SGP2024: youtube.com/watch?v=1u-5b4…

If you're at #SIGGRAPH2024, I will be giving a talk on "Repulsive Shells" tomorrow (Thursday) in the Geometry: Editing and Deformation session, which begins at 10:45am in Mile High 2A.

Signed distance functions (SDFs) are an important surface representation, which can be directly visualized via the “sphere tracing” algorithm. At #SIGGRAPH2024 we showed how to sphere trace a whole new class of surfaces, based on *harmonic functions* rather than SDFs. [1/n]

🔍Need efficient distance queries for 2D/3D meshes? Check out FCPW – a user-friendly library in C++ and Python with GPU support! 💻 Get started here: github.com/rohan-sawhney/… Also available on PyPI: pip install fcpw🐍

Signed distance functions (SDFs) are fundamental tools in graphics, vision, and physics simulation. But how do you get a high-quality SDF from messy, real-world input? At #SIGGRAPH2024, we introduced a simple method for turning "broken" geometry into a well-behaved SDF. <🧵>

If you’re interested in generalized signed distance functions but didn’t make it to our SIGGRAPH talk, I’ve recorded my presentation: youtube.com/watch?v=IzBY-j… Look for official code releases in the coming weeks!

OpenAI's new 4o image generation is pretty amazing. It also fails on some utterly basic tasks. Maybe a good metaphor for how easily we can be misled by algorithms based largely on fitting empirical data (i.e., machine learning) rather than deductive reasoning. Penrose