Research Scientist @GoogleAI #GoogleResearch. PhD in CS @GRASPlab, @Penn. Interested in computer vision and machine learning.
Joined February 2018
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Introducing "Spectrally-Guided Diffusion Noise Schedules", accepted to #ICML2026! With @kiamada.
We propose noise schedules that follow the power spectrum of each image, improving pixel diffusion quality and requiring fewer denoising steps.
At test time, we conditionally sample the spectrum before generating the image.
Denoising is conditioned on the spectrum, which allows manipulating properties like the amount of details, as the animations show.
Carlos Esteves retweeted
📢 Diffusion circle at @icmlconf 2026: join us Thursday July 9 at 3:30PM at the information desk / job board, we'll head out from there and find a spot to sit. No agenda, just get together and talk shop.
Please tell your friends and tag people who might be interested! – at Gangnam-gu, Republic of Korea
Carlos Esteves retweeted
If you're at ICML this week, stop by and chat with @_machc to learn about designing noise schedules for diffusion (Wed, 2:30PM, Hall A)
Introducing "Spectrally-Guided Diffusion Noise Schedules", accepted to #ICML2026! With @kiamada.
We propose noise schedules that follow the power spectrum of each image, improving pixel diffusion quality and requiring fewer denoising steps.
At test time, we conditionally sample the spectrum before generating the image.
Denoising is conditioned on the spectrum, which allows manipulating properties like the amount of details, as the animations show.
Carlos Esteves retweeted
An excellent book only requiring undergraduate level with many color figures.
The last chapter is the culmination of this book:
It explains how to build manifolds from group actions and describes symmetric spaces.
We'll present "Spectral Image Tokenizer" at #ICCV2025 later today, afternoon session.
We tokenize the image spectrum, train an autoregressive transformer for coarse-to-fine generation, and show applications to image generation, upsampling and editing.
w/ @kiamada @msuhail153
Our new paper, "Spectral Image Tokenizer", is on arXiv! We train a tokenizer on DWT coefficients
that enables autoregressive coarse-to-fine image generation, w/ applications to multiscale text-to-image, and text-guided editing.
w/ @kiamada, @msuhail153 arxiv.org/abs/2412.09607
Carlos Esteves retweeted
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-for…
Don't miss the upcoming session on "Spectral Image Tokenizer" presented by @_machc, Research Scientist at @Google, on Wednesday January 22nd!
Huge thanks to @AhmadMustafaAn1 for coordinating this event! 💫
Learn more: cohere.com/events/cohere-for…
Carlos Esteves retweeted
Don't miss the upcoming session on "Spectral Image Tokenizer" presented by @_machc, Research Scientist at @Google, on Wednesday January 22nd!
Huge thanks to @AhmadMustafaAn1 for coordinating this event! 💫
Learn more: cohere.com/events/cohere-for…
Our new paper, "Spectral Image Tokenizer", is on arXiv! We train a tokenizer on DWT coefficients
that enables autoregressive coarse-to-fine image generation, w/ applications to multiscale text-to-image, and text-guided editing.
w/ @kiamada, @msuhail153 arxiv.org/abs/2412.09607
Carlos Esteves retweeted
Our Equivariant Vision workshop features five great speakers @erikjbekkers @HaggaiMaron @ninamiolane @_machc, 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 @CongyueD for leading the organization!
equivision.github.io/index.h…
Carlos Esteves retweeted
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… w/ @twmitchel and @kiamada. Hope to see you there!
Carlos Esteves retweeted
After 3 years, it's time for us to start sharing the chapters of the GDL book! ❤️
Also included: companion slides from our @Cambridge_Uni & @UniofOxford courses 🧑🎓
Chapter 1 is out **now**!
More to follow soon 🎉
geometricdeeplearning.com/bo… 📖
@mmbronstein @joanbruna @TacoCohen
Carlos Esteves retweeted
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…
w/@twmitchel & @_machc
Carlos Esteves retweeted
Our workshop "Equivariant Vision: From Theory to Practice" will be hosted at #CVPR2024 in Seattle this summer! @CVPR
Both original and published works are welcome to submit to our workshop!
🔗equivision.github.io/
⏰Deadline: Mar 22, 2024
Carlos Esteves retweeted
We proudly present our 524 page book on equivariant convolutional networks.
Coauthored by Patrick Forré, @erikverlinde and @wellingmax.
maurice-weiler.gitlab.io/#cn…
[1/N]
Carlos Esteves retweeted
Some well-rounded results: @GoogleResearch 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!
Applying computer vision models designed for planar images to data projected on spherical surfaces is challenging. Here we present an open-source library in JAX to solve the challenges of rotation and regular sampling for state-of-the-art performance → goo.gle/46z3vD7
Our blog post on scaling spherical CNNs for scientific applications was just published, check it out!
Applying computer vision models designed for planar images to data projected on spherical surfaces is challenging. Here we present an open-source library in JAX to solve the challenges of rotation and regular sampling for state-of-the-art performance → goo.gle/46z3vD7
Carlos Esteves retweeted
Excited to announce our ICCV’23 paper: “Learning to Transform for Generalizable Instance-wise Invariance”!
sutkarsh.github.io/projects/…
Carlos Esteves retweeted
📢 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
ASIC: Aligning Sparse in-the-wild Image Collections
abs: arxiv.org/abs/2303.16201
project page: kampta.github.io/asic/
