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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 07/09/2026

🎉 Our group is heading to #ECCV2026 in Malmö (September 8–12) with five papers across the main conference and workshops, including one Spotlight! Come find us at the posters, and a big thank you to all our collaborators!

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 19/10/2025

MVGBench: “A Comprehensive Benchmark for Multi-view Generation Models” — measures 3D consistency & image quality for fair comparisons. By Xianghui Xie, Jan Eric Lenssen, Gerard Pons-Moll Project: virtualhumans.mpi-inf.mpg.de/MVGBench/

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 19/10/2025

VITAL: “More Understandable Feature Visualization via Distribution Alignment & Relevant Information Flow.” Fewer artifacts, more faithful internals, scales well. By Ada Görgün, Bernt Schiele, Jonas Fischer Project: adagorgun.github.io/VITAL-Project/

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 19/10/2025

AIM (Highlight 🎉): “Amending Inherent Interpretability via Self-Supervised Masking.” - Promotes genuine features over spurious ones—no extra annotations. By Eyad Alshami, Shashank Agnihotri, Bernt Schiele, Margret Keuper

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 19/10/2025

DIY-SC: “Do It Yourself—Learning Semantic Correspondence from Pseudo-Labels.” - Light-weight adapter on DINOv2 / SD+DINOv2 → SOTA on SPair-71k w/o keypoints. By O. Dünkel, T. Wimmer, C. Theobalt, C. Rupprecht, A. Kortylewski Page: genintel.github.io/DIY-SC

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 19/10/2025

ICCV 2025 🌺 Aloha from Hawaii! MPI-INF (D2) is presenting 4 papers this year (one Highlight). Thread 👇

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 13/07/2025

4/ "🌀Spatial Reasoners for Continuous Variables in Any Domains" by @bartpog.bsky.social, @chriswewer.bsky.social, Bernt Schiele, and @janericlenssen.bsky.social (CODEML Workshop) 🔍 Software framework for training Spatial Reasoning Models in any domain

Image for "🌀Spatial Reasoners for Continuous Variables in Any Domains"

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 13/07/2025

3/ "Pixel-level Certified Explanations via Randomized Smoothing" by @aanani.bsky.social, Tobias Lorenz, Mario Fritz, and Bernt Schiele

Image for "Pixel-level Certified Explanations via Randomized Smoothing"

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 13/07/2025

2/ "Spatial Reasoning with Denoising Models" by @chriswewer.bsky.social, @bartpog.bsky.social, Bernt Schiele, and @janericlenssen.bsky.social 🔍 Can image generators solve visual Sudoku? Naively, no, with sequentialization and the correct order, they can!

Image for "Spatial Reasoning with Denoising Models"

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 13/07/2025

1/ "DCBM: Data-Efficient Visual Concept Bottleneck Models" by @katharinaprasse.bsky.social*, @patrickknab.bsky.social*, Sascha Marton, Christian Bartelt, and @margretkeuper.bsky.social 🔍 Data-efficient CBMs (DCBMs) generate concepts from image regions detected by segmentation or detection models

Image for "DCBM: Data-Efficient Visual Concept Bottleneck Models"

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 13/07/2025

Papers being presented from our group at #ICML2025! Congratulations to all the authors! To know more, visit us in the poster sessions! A 🧵with more details: @icmlconf.bsky.social @mpi-inf.mpg.de

Papers accepted at ICML 2025 from the Computer Vision and Machine Learning Department at the Max Planck Institute for Informatics.

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 05/07/2025

🎉 Congrats to Yue Fan on defending his PhD: "Improving Representation Learning from Data and Model Perspectives: Semi-Supervised Learning and Foundation Models" 🧑‍🎓 He is now at Genmo.ai as a Research Engineer working on video generation! 🚀 More: yue-fan.github.io All the best!

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 26/06/2025

A heart congratulations to the freshly minted Dr. Mattia Segù on successfully defending his PhD, Congratulazioni!!! 🎉 🎓. His thesis is titled: Learning to Track: From Limited Supervision to Long-range Sequence Modeling Checkout his web-page to learn more about his work: mattiasegu.github.io

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

7/ 🧵 Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery Authors: S. Rao, S. Mahajan, M. Böhle, B. Schiele 🔍 Explore sparse autoencoders to automatically extract and name concepts, enabling performance improvements on downstream tasks. 📚 arxiv.org/abs/2407.14499

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

6/ 🧵 3D-WAG: Wavelet-Guided Autoregressive Generation for 3D Shapes Authors: T. Medi*, A. Rampini, P. Reddy, P. K. Jayaraman, M. Keuper 🔍 3D-WAG introduces wavelet-guided autoregressive generation for 3D shapes, aiming for better geometry modeling. 📚 arxiv.org/abs/2411.19037

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

5/ 🧵 Data-Efficient Visual Concept Bottleneck Models Authors: K. Prasse, P. Knab, S. Marton, C. Bartelt, M. Keuper 🔍 Introducing data-efficient visual concept bottleneck models for improved explainability in CV. 📚 arxiv.org/abs/2412.11576

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

4/ 🧵 HD-VILA-Caption: A Diverse Video-Text Dataset Derived from ASR Narrations By: M. Saleh, N. Shvetsova, A. Kukleva, H. Kuehne, B. Schiele 🔍 HD-VILA-Caption is a large-scale, diverse video-text dataset with 10M high-quality captions, built from ASR subtitles for video-language pretraining.

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

3/ 🧵 Corner Cases: How Size and Position of Objects Challenge ImageNet-Trained Models By: M. Fatima, S. Jung, M. Keuper 🔍 Exploring how object size & position affect ImageNet-trained models and lead to performance issues. 📚 openreview.net/forum?id=B6l...

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

2/ 🧵 Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? By: S. Agnihotri, D. Schader, N. Sharei, M.E. Kaçar, M. Keuper 🔍 Investigating if synthetic corruptions can be a reliable proxy for real-world ones, and understanding their limitations. 📚https://www.arxiv.org/abs/2505.04835

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

1/ 🧵 DispBench: Benchmarking Disparity Estimation to Synthetic Corruptions By: S. Agnihotri, A. Ansari, A. Dackermann, F. Rösch, M. Keuper 🔍 A benchmark & tool for testing disparity estimation methods against synthetic corruptions & attacks. 📚 arxiv.org/abs/2505.050...

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

Thread: Workshop Papers from Our Lab at CVPR 2025! 🚀 👏 Huge congrats to our members on these workshop paper acceptances! Excited to see their work at #CVPR2025 🌟 #MPI-INF #D2 #Workshop #AI #ComputerVision #PhD @mpi-inf.mpg.de

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

5/ 🧵 Number it: Temporal Grounding Like Manga Authors: Y. Wu*, X. Hu*, Y. Sun, Y. Zhou, W. Zhu, F. Rao, B. Schiele, X. Yang 🔍 NumPro enhances Video-LLMs in temporal grounding with red number markers, like flipping manga! 📚 arxiv.org/abs/2411.10332

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

4/ 🧵 PersonaHOI: Face Personalization in Human-Object Interaction By: X. Hu*, H. Wang*, J.E. Lenssen, B. Schiele 🔍 PersonaHOI is the first training-free framework to generate human-object interactions with personalized faces. 📚 arxiv.org/abs/2501.05823

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

3/ 🧵 MEt3R: Measuring Multi-View Consistency By: M. Asim, C. Wewer, T. Wimmer, B. Schiele, J.E. Lenssen 🔍 MEt3R is a metric for multi-view consistency in generated image sequences & videos. 📚 arxiv.org/abs/2501.06336 🔗 geometric-rl.mpi-inf.mpg.de/met3r/

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

2/ 🧵 Unbiasing through Textual Descriptions By: N. Shvetsova, A. Nagrani, B. Schiele, H. Kuehne, C. Rupprecht 🔍 UTD uses VLMs/LLMs to mitigate representation bias in video benchmarks, ensuring fairer evaluations. 📚 arxiv.org/abs/2503.18637 📱 @ninashv.bsky.social @hildekuehne.bsky.social

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

1/ 🧵 Test-Time Visual In-Context Tuning By: J. Xie, A. Tonioni, N. Rauschmayr, F. Tombari, B. Schiele 🔍 VICT adapts VICL models with a single test sample, enhancing generalizability for unseen tasks. 📚 arxiv.org/abs/2503.21777 🔗 github.com/Jiahao000/VICT

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

Thread: Main Conference Papers from Our Lab at CVPR 2025! 🚀 👏 Big congrats to everyone! Keep an eye out at #CVPR2025 🌟 #MPI-INF #D2 #ComputerVision #AI #PhD #ML @mpi-inf.mpg.de

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/06/2025

🎉 Exciting News #CVPR2025! We’re proud to announce that we have 5 papers accepted to the main conference and 7 papers accepted at various CVPR workshops this year! We’re looking forward to sharing our research with the community in Nashville! Stay tuned for more details! ‪‪@mpi-inf.mpg.de‬

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Computer Vision and Machine Learning at MPI Informatics @cvml.mpi-inf.mpg.de · 11/04/2025

Congratulations to Max Losch for successfully defending his PhD! 🥳🎉🎓 In his thesis, "Improving Trustworthiness of Deep Learning via Inspectable and Robust Representations", he explores transparency and robustness of deep networks. We wish him the best!

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