iiinova — where your digital self keeps evolving

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 03/06/2026

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation (Sun 15:30pm, Poster #658) bsky.app/profile/joh-...

010

Reposted by CompVis - Computer Vision and Learning LMU Munich

Johannes Schusterbauer @joh-schb.bsky.social · 26/05/2026

Diffusion models treat every part of an image equally. → Same number of steps. Same compute. But images aren’t uniform. 🤔 Some regions are easy, others are hard. So why force the model to treat them the same? 🧵

12812

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 03/06/2026

Learning Long-term Motion Embeddings for Efficient Kinematics Generation (Sun 15:30pm, Poster #595) bsky.app/profile/rmsn...

200

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 03/06/2026

EDGS: Eliminating Densification for Efficient Convergence of 3DGS (Sun 15:30pm, Poster #453) compvis.github.io/EDGS/

compvis.github.io

EDGS

EDGS: Eliminating Densification for Efficient Convergence of 3DGS

100

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 03/06/2026

Envisioning the Future, One Step at a Time (Fri 10:45am, Poster #634) bsky.app/profile/stef...

100

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 03/06/2026

Six papers from CompVis @ LMU accepted to #CVPR2026! Looking forward to presenting, catching up with folks whose work we've been reading all year, and seeing what the rest of the community is up to. If you're there, come find us! Paper threads 👇

120

Reposted by CompVis - Computer Vision and Learning LMU Munich

Munich Center for Machine Learning @munichcenterml.bsky.social · 28/04/2026

🎬 “AI should be a tool that empowers everyone, not just those with the most computing power.” #MCML PI Björn Ommer explains why democratizing AI was the driving force behind the development of Stable Diffusion. 👉 Watch the video: youtu.be/xuBRRItRmsg

youtu.be

Prof. Björn Ommer: How AI can transform society if we use it responsibly

YouTube video by MCML_Munich Center for Machine Learning

032

Reposted by CompVis - Computer Vision and Learning LMU Munich

Nick Stracke @rmsnorm.bsky.social · 14/04/2026

Video diffusion models learn motion indirectly through pixels. But motion itself is much lower-dimensional. We introduce 64× temporally compressed motion embeddings that directly capture scene dynamics. This enables efficient planning -> 10,000× faster than video models. 🧵👇

1142

Reposted by CompVis - Computer Vision and Learning LMU Munich

Stefan Baumann @stefanabaumann.bsky.social · 13/04/2026

You don't imagine the future by mentally rendering a movie. You trace how things move -- abstractly, sparsely, step by step. We built a model that does exactly this. It predicts motion, not pixels -- and it's 3,000× faster than video world models. Myriad, accepted at @cvprconference.bsky.social

2259

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 19/10/2025

Finally, Felix will present his work on making diffusion transformer training extremely efficient, going from costing multiple months of rent to less than a single night at a conference hotel! compvis.github.io/tread/

compvis.github.io

TREAD: Token Routing for Efficient Architecture-agnostic Diffusion Training

010

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 19/10/2025

Stefan and Timy will be talking about how we can achieve extremely efficient motion prediction in open-set settings: bsky.app/profile/stef...

110

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 19/10/2025

Pingchuan and Ming will be presenting two works on modeling the evolution of artistic style and disentangled representation learning. See the following thread for more details bsky.app/profile/pima...

110

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 19/10/2025

Excited to share that we'll be presenting four papers at the main conference at ICCV 2025 this week! Come say hi in Honolulu! 👋 Pingchuan, Ming, Felix, Stefan, Timy, and Björn Ommer will be attending.

121

Reposted by CompVis - Computer Vision and Learning LMU Munich

ELLIOT Project @elliot-eu.bsky.social · 17/10/2025

🎉 From @elsa-ai.eu: 15 new members join the European Lighthouse on Secure & Safe AI—expanding reach across Europe and deepening ties with the @ellis.eu ecosystem. Everything you need to know 👉 elsa-ai.eu/elsa-welcome...

032

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 17/10/2025

Fascinating approach — encoding an entire image into a single continuous latent token via self-supervised representation learning. RepTok 🦎 highlights how compact generative representations can retain both realism and semantic structure.

020

Reposted by CompVis - Computer Vision and Learning LMU Munich

Stefan Baumann @stefanabaumann.bsky.social · 15/10/2025

🤔 What happens when you poke a scene — and your model has to predict how the world moves in response? We built the Flow Poke Transformer (FPT) to model multi-modal scene dynamics from sparse interactions. It learns to predict the 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯 of motion itself 🧵👇

1248

Reposted by CompVis - Computer Vision and Learning LMU Munich

Munich Center for Machine Learning @munichcenterml.bsky.social · 10/10/2025

𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗳𝘂𝗹𝗹𝘆 𝗳𝘂𝗻𝗱𝗲𝗱 𝗣𝗵𝗗 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝘀: We are offering several PhD positions across our various research areas, open to highly qualified candidates. ‼️ The application portal will be open from 15 October to 14 November 2025. Find out more: mcml.ai/opportunitie...

066

Reposted by CompVis - Computer Vision and Learning LMU Munich

ELLIOT Project @elliot-eu.bsky.social · 03/07/2025

🎧 ELLIOT on the airwaves! How do we build open and trustworthy AI in Europe? 🎙️ In a recent radio interview, Luk Overmeire from VRT shared insights on ELLIOT, #FoundationModels and the role of public broadcasters in shaping human-centred AI. 📻 Interview in Dutch: mimir.mjoll.no/shares/JRqlO...

011

Reposted by CompVis - Computer Vision and Learning LMU Munich

Munich Center for Machine Learning @munichcenterml.bsky.social · 08/07/2025

"What makes us human in an AI-shaped world?" — At #MCML Munich AI Day 2025, Neil Lawrence explored this question, reminding us of the indivisible human core machines can't replicate. Björn Ommer followed with insights into how GenAI is commodifying intelligence and reshaping how we use computers.

001

Reposted by CompVis - Computer Vision and Learning LMU Munich

ELLIOT Project @elliot-eu.bsky.social · 11/07/2025

🎉 The ELLIOT project Kick-off Meeting was successfully hosted by CERTH-ITI, in Thessaloniki! 🏛️ 30 partners from 12 countries 🌍 launched this exciting journey to advance open, trustworthy AI and #FoundationModels across Europe. 🤖 Stay tuned for more updates on #AIresearch and #TrustworthyAI! 💡

043

Reposted by CompVis - Computer Vision and Learning LMU Munich

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 09/06/2025

🧹 CleanDiFT: Diffusion Features without Noise @rmsnorm.bsky.social*, @stefanabaumann.bsky.social*, @koljabauer.bsky.social*, @frankfundel.bsky.social, Björn Ommer Oral Session 1C (Davidson Ballroom): Friday 9:00 Poster Session 1 (ExHall D): Friday 10:30-12:30, # 218 compvis.github.io/cleandift/

compvis.github.io

CleanDIFT: Diffusion Features without Noise

CleanDIFT enables extracting Noise-Free, Timestep-Independent Diffusion Features

183

Reposted by CompVis - Computer Vision and Learning LMU Munich

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 09/06/2025

🎉 Excited to share that our lab has three papers accepted at CVPR 2025! Come say hi in Nashville! 👋 Johannes, Ming, Kolja, Stefan, and Björn will be attending.

112

Reposted by CompVis - Computer Vision and Learning LMU Munich

ELLIOT Project @elliot-eu.bsky.social · 12/06/2025

📢 ELLIOT is coming! A €25M #HorizonEurope project to develop open, trustworthy Multimodal Generalist Foundation Models, #MGFM, for real-world applications. Starting July, it brings 30 partners from 12 countries to shape Europe’s #AI future. 🔍 Follow for updates on #OpenScience & #FoundationModels.

054

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 09/06/2025

Continuous Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions @stefanabaumann.bsky.social, Felix Krause, Michael Neumayr, @rmsnorm.bsky.social, Melvin Sevi, @vtaohu.bsky.social, Björn Ommer P. Sess 3 (ExHall D): Sat 10:30-12:30, #246 compvis.github.io/attribute-co...

compvis.github.io

Subject-Specific Concept Control

We reveal that certain directions in CLIP text embeddings permit detailed attribute control in text-to-image models.

020

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 09/06/2025

compvis.github.io

CleanDIFT: Diffusion Features without Noise

CleanDIFT enables extracting Noise-Free, Timestep-Independent Diffusion Features

183

CompVis - Computer Vision and Learning LMU Munich @compvis.bsky.social · 09/06/2025

🎉 Excited to share that our lab has three papers accepted at CVPR 2025! Come say hi in Nashville! 👋 Johannes, Ming, Kolja, Stefan, and Björn will be attending.

112

Reposted by CompVis - Computer Vision and Learning LMU Munich

Munich Center for Machine Learning @munichcenterml.bsky.social · 20/01/2025

Grand Opening of the AI-HUB@LMU. The AI-HUB@LMU is a platform that for the first time unites all 18 faculties of the #LMU as a joint scientific community. 📅January 29, 2025, 6:00 PM 📍 Große Aula, LMU Munich Full program here: www.ai-news.lmu.de/grand-openin...

041

Reposted by CompVis - Computer Vision and Learning LMU Munich

Alexander Wuttke @kunkakom.bsky.social · 16/01/2025

Attending my first corporate-sponsored business conference: there’s a live band playing between talks to keep the energy up. Meanwhile, academic conferences are struggling to afford coffee breaks. Want this for EPSA! @compvis.bsky.social

181

Reposted by CompVis - Computer Vision and Learning LMU Munich

Pingchuan Ma @pima-hyphen.bsky.social · 08/01/2025

🤔When combining Vision-language models (VLMs) with Large language models (LLMs), do VLMs benefit from additional genuine semantics or artificial augmentations of the text for downstream tasks? 🤨Interested? Check out our latest work at #AAAI25: 💻Code and 📝Paper at: github.com/CompVis/DisCLIP 🧵👇

1158

Reposted by CompVis - Computer Vision and Learning LMU Munich

Frank Fundel @frankfundel.bsky.social · 06/12/2024

Did you know you can distill the capabilities of a large diffusion model into a small ViT? ⚗️ We showed exactly that for a fundamental task: semantic correspondence📍 A thread 🧵👇

142

Reposted by CompVis - Computer Vision and Learning LMU Munich

Nick Stracke @rmsnorm.bsky.social · 04/12/2024

🤔 Why do we extract diffusion features from noisy images? Isn’t that destroying information? Yes, it is - but we found a way to do better. 🚀 Here’s how we unlock better features, no noise, no hassle. 📝 Project Page: compvis.github.io/cleandift 💻 Code: github.com/CompVis/clea... 🧵👇

24210