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Visual Inference Lab of @stefanroth at @TUDarmstadt. Research in Computer Vision and Machine Learning.

Darmstadt, Germany
Joined April 2012
Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)Photo by Visual Inference Lab (@visinf)
Visual Inference Lab retweeted
I am looking for motivated PhD students, and now you can connect through the Vector Graduate Student Program!
The standard graduate application process is backward. You spend months researching programs, navigating faculty pages, and emailing professors who may or may not respond. You pay hundreds of dollars in application fees. Then you wait to find out if a lab actually has space, funding, or any interest in your research. Great AI research starts with the right supervisor match. The process should too. 🧵
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Visual Inference Lab retweeted
📢 LucidLyra: Feed-Forward Generative 3D Scene Reconstruction and Joint Understanding via Multi-Task Distillation! Generate a queryable 3D Gaussian scene from a single image! Our feed-forward decoder jointly predicts geometry, appearance, open-vocabulary semantics, and object instances. We train on generated videos, combining video-model self-distillation with supervision from frozen 2D vision foundation models. LucidLyra enables applications such as physical AI simulation, 3D scene editing, and 3D asset mining. 🌍 research.nvidia.com/labs/sil…
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Visual Inference Lab retweeted
🚨 Apply now for the #ELLISPhD Program! Work with leading AI/ML researchers across Europe, with exchange visits & joint supervision. The application deadline is 31 Oct. Get all info & apply now at ellis.eu/news/ellis-phd-prog…
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I wrote a blog sharing some thoughts after spending the last days looking more carefully at the GPT-6 Astra results in robotics, 3D, CAD and autonomous experimentation. I started rather skeptical, and I still don’t think these results mean that scaling has suddenly “solved robotics.” But I do think something interesting is happening. What capability are we actually seeing? What role does structure play? What is learned by the model, and what becomes possible because of the tools, representations and algorithms around it? And perhaps most importantly, what experiments do we actually need to answer these questions? What Are We Actually Seeing with GPT-6 Astra? #Robotics #GPT6 #Astra #RobotLearning nitter.cf/GeorgiaChal/status/210…
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1/6 🧵 ReconSplat: Generalizable 3D Scene Reconstruction Beyond Observed Views by @GpStracquadanio, Kevin Raj, @JuliaGrabinski, @stefanroth 📍 Thursday Poster Session 1 @ECCV Poster #196
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5/6 ☁️ From novel views to 3D reconstructions. We can unproject our predictions into point clouds, revealing sharp and consistent geometry, even *beyond the observed views*. ✨ Jointly generating appearance and geometry lets us complete scenes in 3D.
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Visual Inference Lab retweeted
Dinner with the keynote speakers and organizers of the #ECCV2026 Workshop on Explainable Computer Vision. Thank you @sukrutrao @AdaGorgun @schaub_simone Stephan Alaniz @Amin_Prc for the invitation! Great hanging out with @LilyWeng_ @HildeKuehne my fellow speakers too!
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[1/6] 📢 We are in Malmö at #ECCV2026 presenting 5 papers! 🎉
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[5/6] LeAD-M3D: Leveraging Asymmetric Distillation for Real-Time Monocular 3D Detection J. Meier*, J. Michel*, O. Dhaouadi, @YungHsuYang, @ChristophReich1996, @zuriich92, @stefanroth, @mapo1, J. Kaiser, D. Cremers (@tumcvg) 🌍 Project Page: deepscenario.github.io/LeAD-…
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Visual Inference Lab retweeted
Had so much fun at #CVPR2026! 🎉 Really happy to have presented two papers this year and discussed them with so many people. Both projects came out of my time at @visinf, TU Darmstadt, last year. Very grateful to @stefanroth for hosting me and helping shape them from the beginning, and to all my co-authors for being part of this 😊
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Visual Inference Lab retweeted
INSID3 segments objects across domains using ONLY ONE annotated example it works entirely without a segmentation decoder, task-specific fine-tuning, or external mask generators like SAM CVPR 2026 paper with enormous practical potential
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