Computer Vision and Machine Learning at MPI Informatics

Computer Vision and Machine Learning at MPI Informatics

cvml.mpi-inf.mpg.de

Computer Vision and Machine Department at the Max Planck Institute for Informatics | https://www.mpi-inf.mpg.de/departments/computer-vision-and-machine-learning/

👤 Joined on 12 March 2025

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📜 Kullanıcı Geçmişi

  • 12 Mar 2025, 15:18
    🎉 Bluesky'e katıldı - İlk kullanıcı adı: @cvml.bsky.social
  • 13 Mar 2025, 10:05
    ✏️ Kullanıcı adı değişti: @cvml.bsky.social → @cvml.mpi-inf.mpg.de

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Sid
10 February 2026 13:48

🚀New preprint: DAVE — Distribution-aware Attribution via ViT Gradient DEcomposition. 1/11 🔍 What’s new: We fix a persistent issue in ViT explainability: unstable, artifact-heavy pixel attributions. DAVE yields fine-grained pixel-level maps without patch-grid saliency.

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As poster sessions wrap up in Mexico City, we're grateful for the incredible research shared and connections made. Thank you to everyone who made our CDMX venue such a vibrant part of NeurIPS 2025! 🇲🇽 #NeurIPS2025 #NeurIPSCDMX

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#ICCV2025
19 October 2025 07:54

ICCV 2025 kicks off tomorrow! We look forward to welcoming everyone to Hawaii 🌺

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Olaf Dünkel
19 October 2025 07:43

Are you using DINOv2 for tasks that require semantic features? DIY-SC might be the alternative! It refines DINOv2 or SD+DINOv2 features and achieves a new SOTA on the semantic correspondence dataset SPair-71k when not relying on annotated keypoints! [1/6] genintel.github.io/DIY-SC

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Super excited to introduce ✨ AnyUp: Universal Feature Upsampling 🔎 Upsample any feature - really any feature - with the same upsampler, no need for cumbersome retraining. SOTA feature upsampling results while being feature-agnostic at inference time. 🌐 wimmerth.github.io/anyup/

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