In this Google AI Blog post, we summarize our recent contributions on neural rendering with transformers. Check it out! Ameesh Makadia Suhail Mohammed

Ameesh Makadia’s first vision conference was ECCV 2002 in Copenhagen. So proud to see him present their “Generalized patch-based rendering” with our Carlos ⁦Carlos Esteves⁩, Sigal and Suhail at #eccv2022 today.

Applications for the first-ever Google PhD Fellowships for students in Latin America open today, along with applications to support early-career professors through Research Scholar. Read more about our investments in the Latin American research ecosystem ↓goo.gle/3Gz3bKU

Scaling Spherical CNNs paper page: huggingface.co/papers/2306.05… Spherical CNNs generalize CNNs to functions on the sphere, by using spherical convolutions as the main linear operation. The most accurate and efficient way to compute spherical convolutions is in the spectral domain

I'll present "Scaling Spherical CNNs" at #ICML2023 today 11am, Exhibit Hall 1 #215. Happy to chat anytime during the conference!

The weather forecast is improving… literally! Introducing WeatherBench 2, a benchmark for the next generation of data-driven, global weather forecast models, providing data, tools, & an evaluation platform. Learn how to use it and check out the website →goo.gle/3YVUGAU

📢 Join us as we present ASIC at #ICCV2023 on Wed! We propose a method for dense correspondence that DOES NOT need tons of data/3D priors/manual annotations! How do we do it? Check out the 🧶 and visit Oral: Wed 4:30-6:00 PM Poster: Wed 2:30-4:30 PM Web: github.com/kampta/asic

Excited to announce our ICCV’23 paper: “Learning to Transform for Generalizable Instance-wise Invariance”! sutkarsh.github.io/projects/learn…

Our blog post on scaling spherical CNNs for scientific applications was just published, check it out!

Some well-rounded results: Google Research work shows that deep learning on a sphere -- instead of flat space -- is superior for things like prediction of weather & molecular properties. Consider spherical surfaces (much better than pretending the world is flat!). See JAX code!

We proudly present our 524 page book on equivariant convolutional networks. Coauthored by Patrick Forré, Erik Verlinde and Max Welling. maurice-weiler.gitlab.io/#cnn_book [1/N]

Our workshop "Equivariant Vision: From Theory to Practice" will be hosted at #CVPR2024 in Seattle this summer! #CVPR2026 Both original and published works are welcome to submit to our workshop! 🔗equivision.github.io ⏰Deadline: Mar 22, 2024

Generate high quality textures with single mesh LDMs! #CVPR2024 Our *intrinsic* 3D diffusion models, trained on a single mesh, can generate texture variations, perform inpainting, and even transfer textures to different shapes. single-mesh-diffusion.github.io w/Tommy Mitchel & Carlos Esteves

After 3 years, it's time for us to start sharing the chapters of the GDL book! ❤️ Also included: companion slides from our Cambridge University & University of Oxford courses 🧑‍🎓 Chapter 1 is out **now**! More to follow soon 🎉 geometricdeeplearning.com/book 📖 Michael Bronstein @joanbruna Taco Cohen

I've never used this website for this but let's try: I'm on the lookout for full-time positions. The more research it involves the better. Open to both industrial and academic positions. If you know of good openings, my DMs are open, and I'll send my CV! PS: I'm on an O1-A visa.

At #CVPR2024, I will give a talk about "Geometric Deep Learning for Weather" at the Equivariant Vision workshop Tue 2pm equivision.github.io, and I'll present a poster on Single Mesh Diffusion Wed 5pm single-mesh-diffusion.github.io w/ Tommy Mitchel and Ameesh Makadia. Hope to see you there!

Our Equivariant Vision workshop features five great speakers Erik Bekkers Haggai Maron Nina Miolane 🦋 @ninamiolane.bsky.social Carlos Esteves, and Leo Guibas, spotlight talks, posters, and a tutorial prepared for the vision audience. Come tomorrow, Tuesday, at 8:30am in Summit 321! Thank you Congyue Deng for

Don't miss the upcoming session on "Spectral Image Tokenizer" presented by Carlos Esteves, Research Scientist at Google, on Wednesday January 22nd! Huge thanks to Ahmad Mustafa Anis for coordinating this event! 💫 Learn more: cohere.com/events/cohere-…

We can't wait to welcome Carlos Esteves, Research Scientist at Google, tomorrow, January 22nd for a session on "Spectral Image Tokenizer." 🗓️ Learn more and add this event to your calendar: cohere.com/events/cohere-…