Can we apply gradient descent to discrete changes? In our new #SIGGRAPHAsia paper, we show that gradient descent can work on shape grammars, as in CAD and procedural modeling, but only if the grammars are designed correctly!
We show that these properties matter through ablations over grammar variants and compare against existing random-walk approaches like RJMCMC. Grammars that satisfy more of our guidelines consistently converge faster and reach better optima.
Jack was one of the first students in our group 3DL! He did a couple of awesome works with us during his undergrad. Check out his papers and make sure to follow his journey as he starts as a PhD student in @uwcse with @AdrianaSchulz7 ! zzhang-18.github.io/
One thing that makes siggraph unique is that it’s so much more than just technical papers. I’m excited that @UChicagoCS will be active across several different forums: technical papers, workshops, emerging technologies, frontiers talks, and even a social meetup! Come meet us 🤩
Thrilled to share "GANimator: Neural Motion Synthesis from a Single Sequence", in this upcoming #SIGGRAPH2022 🤩
GANimator can produce novel animations for unique creatures that don't have large motion datasets! For example, this hexapedal crab 🦀(1/4)