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Dominik Schnaus

@schnaus.bsky.social
118 followers 415 following 4 posts

PhD student @ TUM with Daniel Cremers

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Reposted by Dominik Schnaus
A. Sophia Koepke @askoepke.bsky.social · 17/04/2026
New paper: Back into Plato’s Cave Are vision and language models converging to the same representation of reality? The Platonic Representation Hypothesis says yes. BUT we find the evidence for this is more fragile than it looks. Project page: akoepke.github.io/cave_umwelten/ 1/9
akoepke.github.io
Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale
Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale
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Reposted by Dominik Schnaus
Munich Center for Machine Learning @munichcenterml.bsky.social · 16/01/2026
𝗠𝗖𝗠𝗟 𝗕𝗹𝗼𝗴: Images and text are usually aligned using millions of image–caption pairs. But could they still be matched if they were never seen together? In “It’s a (Blind) Match!”, MCML Members explore this question. mcml.ai/news/2026-01...
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Reposted by Dominik Schnaus
Christoph Reich @christophreich.bsky.social · 09/07/2025
🦖 We present “Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion”. #ICCV2025 🌍: visinf.github.io/scenedino/ 📃: arxiv.org/abs/2507.06230 🤗: huggingface.co/spaces/jev-a... @jev-aleks.bsky.social @fwimbauer.bsky.social @olvrhhn.bsky.social @stefanroth.bsky.social @dcremers.bsky.social
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Linus Härenstam-Nielsen @linushn.bsky.social · 09/07/2025
The code for our #CVPR2025 paper, PRaDA: Projective Radial Distortion Averaging, is now out! Turns out distortion calibration from multiview 2D correspondences can be fully decoupled from 3D reconstruction, greatly simplifying the problem arxiv.org/abs/2504.16499 github.com/DaniilSinits...
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Dominik Schnaus @schnaus.bsky.social · 03/06/2025
Can we match vision and language representations without any supervision or paired data? Surprisingly, yes!  Our #CVPR2025 paper with @neekans.bsky.social and @dcremers.bsky.social shows that the pairwise distances in both modalities are often enough to find correspondences. ⬇️ 1/4
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Felix Wimbauer @fwimbauer.bsky.social · 13/05/2025
Can you train a model for pose estimation directly on casual videos without supervision? Turns out you can! In our #CVPR2025 paper AnyCam, we directly train on YouTube videos and achieve SOTA results by using an uncertainty-based flow loss and monocular priors! ⬇️
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Reposted by Dominik Schnaus
Felix Wimbauer @fwimbauer.bsky.social · 23/04/2025
Check out our latest recent #CVPR2025 paper AnyCam, a fast method for pose estimation in casual videos! 1️⃣ Can be directly trained on casual videos without the need for 3D annotation. 2️⃣ Based around a feed-forward transformer and light-weight refinement. Code and more info: ⏩ fwmb.github.io/anycam/
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Daniel Cremers @dcremers.bsky.social · 13/03/2025
We are thrilled to have 12 papers accepted to #CVPR2025. Thanks to all our students and collaborators for this great achievement! For more details check out cvg.cit.tum.de
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Reposted by Dominik Schnaus
Daniel Cremers @dcremers.bsky.social · 16/01/2025
Indeed - everyone had a blast - thank you all for the great talks, discussions and Ski/snowboarding!
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