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/
114 followers39 following51 posts
Computer Vision and Machine Learning at MPI Informatics reposted
Computer Vision and Machine Learning at MPI Informatics reposted
MVGBench: โA Comprehensive Benchmark for Multi-view Generation Modelsโ โ measures 3D consistency & image quality for fair comparisons. By Xianghui Xie, Jan Eric Lenssen, Gerard Pons-Moll Project: virtualhumans.mpi-inf.mpg.de/MVGBench/
VITAL: โMore Understandable Feature Visualization via Distribution Alignment & Relevant Information Flow.โ Fewer artifacts, more faithful internals, scales well. By Ada Gรถrgรผn, Bernt Schiele, Jonas Fischer Project: adagorgun.github.io/VITAL-Project/
DIY-SC: โDo It YourselfโLearning Semantic Correspondence from Pseudo-Labels.โ - Light-weight adapter on DINOv2 / SD+DINOv2 โ SOTA on SPair-71k w/o keypoints. By O. Dรผnkel, T. Wimmer, C. Theobalt, C. Rupprecht, A. Kortylewski Page: genintel.github.io/DIY-SC
Computer Vision and Machine Learning at MPI Informatics reposted
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
Computer Vision and Machine Learning at MPI Informatics reposted
Super excited to introduce โจ AnyUp: Universal Feature Upsampling ๐ 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. ๐ wimmerth.github.io/anyup/
Computer Vision and Machine Learning at MPI Informatics reposted
๐จ Call for Questions! ๐จ We are inviting the community and the stakeholders to submit questions, which will be discussed with our experts at the workshop! ๐ค๐ก ๐ Submit your questions: forms.gle/8cYb4Ce3dGHi... Workshop: excv-workshop.github.io @iccv.bsky.social #ICCV2025 #eXCV
Computer Vision and Machine Learning at MPI Informatics reposted
Kurt Mehlhorn, Founding Director of MPI for Informatics, was awarded the Saarland Order of Merit yesterday by Minister President Anke Rehlinger. The award recognizes his lifeโs work, from advancing algorithmic research to mentoring researchers and helping build key institutions. More: sic.link/merit
Computer Vision and Machine Learning at MPI Informatics reposted
Are you an XAI researcher attending #ICCV2025? Submit your recently published work โ at CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI etc. โ to the eXCV Workshop for the opportunity to further showcase your work! Published papers can be submitted as is, no rewriting necessary. @iccv.bsky.social
Computer Vision and Machine Learning at MPI Informatics reposted
๐ UTD is now fully released! Code โ Models โ 2M video descriptions โ Debiased splits for 12 datasets โ Everything you need to benchmark video models more fairly is now public: ๐ github.com/ninatu/utd-p... ๐ฅ Letโs make video understanding actually about video understanding.
Computer Vision and Machine Learning at MPI Informatics reposted
People often use synthetic corruptions to test model robustness, but do these reflect real-world challenges? We explore this in detail in our CVPR 2025 Workshop paper: Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions? arxiv.org/abs/2505.04835 by: @margretkeuper.bsky.social
Computer Vision and Machine Learning at MPI Informatics reposted
๐จDeadline Extension Alert! Our Non-proceedings track is open till August 15th for the eXCV workshop at ICCV. Our nectar track accepts published papers, as is. More info at: excv-workshop.github.io @iccv.bsky.social #ICCV2025
Computer Vision and Machine Learning at MPI Informatics reposted
โณStill need to wait for your last experiment results? ๐ฃ We're pleased to announce that the deadline for non-proceeding track #CV4DC at @iccv.bsky.social has been extended to August 15, 2025 Looking forward to your submissions! cv4dc.github.io/2025/
๐ฃ Proceeding track's results are out. ๐ Congratulations to all the authors whose papers were accepted. We can't wait to meet you at @iccv.bsky.social in Hawaii on Oct 19th. โฐ Our non-proceeding track is still accepting submissions until July 20th! Details in the comments
Papers being presented from our group at #ICML2025! Congratulations to all the authors! To know more, visit us in the poster sessions! A ๐งตwith more details: @icmlconf.bsky.social @mpi-inf.mpg.de
4/ "๐Spatial Reasoners for Continuous Variables in Any Domains" by @bartpog.bsky.social, @chriswewer.bsky.social, Bernt Schiele, and @janericlenssen.bsky.social (CODEML Workshop) ๐ Software framework for training Spatial Reasoning Models in any domain
Papers being presented from our group at #ICML2025! Congratulations to all the authors! To know more, visit us in the poster sessions! A ๐งตwith more details: @icmlconf.bsky.social @mpi-inf.mpg.de
3/ "Pixel-level Certified Explanations via Randomized Smoothing" by @aanani.bsky.social, Tobias Lorenz, Mario Fritz, and Bernt Schiele
๐ Can you really trust the explanations your classifier gives you? We show which pixels in the input are provably important to the classifierโs prediction within a radius around the input. ๐ openreview.net/pdf?id=NngoE... ๐ github.com/AlaaAnani/ce...
Papers being presented from our group at #ICML2025! Congratulations to all the authors! To know more, visit us in the poster sessions! A ๐งตwith more details: @icmlconf.bsky.social @mpi-inf.mpg.de
2/ "Spatial Reasoning with Denoising Models" by @chriswewer.bsky.social, @bartpog.bsky.social, Bernt Schiele, and @janericlenssen.bsky.social ๐ Can image generators solve visual Sudoku? Naively, no, with sequentialization and the correct order, they can!
Papers being presented from our group at #ICML2025! Congratulations to all the authors! To know more, visit us in the poster sessions! A ๐งตwith more details: @icmlconf.bsky.social @mpi-inf.mpg.de
1/ "DCBM: Data-Efficient Visual Concept Bottleneck Models" by @katharinaprasse.bsky.social*, @patrickknab.bsky.social*, Sascha Marton, Christian Bartelt, and @margretkeuper.bsky.social ๐ Data-efficient CBMs (DCBMs) generate concepts from image regions detected by segmentation or detection models
Computer Vision and Machine Learning at MPI Informatics reposted
๐ฃ Proceeding track's results are out. ๐ Congratulations to all the authors whose papers were accepted. We can't wait to meet you at @iccv.bsky.social in Hawaii on Oct 19th. โฐ Our non-proceeding track is still accepting submissions until July 20th! Details in the comments
๐ Congrats to Yue Fan on defending his PhD: "Improving Representation Learning from Data and Model Perspectives: Semi-Supervised Learning and Foundation Models" ๐งโ๐ He is now at Genmo.ai as a Research Engineer working on video generation! ๐ More: yue-fan.github.io All the best!
Congratulations to our PhD alumna @annakukleva.bsky.social for being awarded the prestigious Otto Hahn Medal by @maxplanck.de! ๐
Congrats to @annakukleva.bsky.social, for winning the Otto Hahn Medal of @maxplanck.de! ๐ In her PhD thesis she shows how AI can learn to recognize images & videos with less manual labeling, using self-supervised and weakly supervised methods. โช๏ธ sic.link/ottohahn25 #AI #ComputerVision #research
Computer Vision and Machine Learning at MPI Informatics reposted
๐ Just accepted to ICCV 2025! In DIY-SC, we improve foundational features using a light-weight adapter trained with carefully filtered and refined pseudo-labels. ๐ง Drop-in alternative to plain DINOv2 features! ๐ฆ Code + pre-trained weights available now. ๐ฅ Try it in your next vision project!
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
Computer Vision and Machine Learning at MPI Informatics reposted
Submission Deadline is extended by 6 days. #ICCV2025 @iccv.bsky.social
Join us in advancing explainability in the rapidly evolving landscape of AI! We welcome papers on novel explanation methods, scaling existing xAI approaches, innovations for foundational models, and beyond.
A heart congratulations to the freshly minted Dr. Mattia Segรน on successfully defending his PhD, Congratulazioni!!! ๐ ๐. 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
Computer Vision and Machine Learning at MPI Informatics reposted
Join us in taking stock of the state of the field of explainability in computer vision, at our Workshop on Explainable Computer Vision: Quo Vadis? at #ICCV2025! @iccv.bsky.social
Computer Vision and Machine Learning at MPI Informatics reposted
At #CVPR2025 and working on consistency in video and multi-view generative models? Come and visit our poster on Friday afternoon, where I present ๐ ๐๐๐ฏ๐ฅ: ๐ ๐ฒ๐ฎ๐๐๐ฟ๐ถ๐ป๐ด ๐ ๐๐น๐๐ถ-๐ฉ๐ถ๐ฒ๐ ๐๐ผ๐ป๐๐ถ๐๐๐ฒ๐ป๐ฐ๐ ๐ถ๐ป ๐๐ฒ๐ป๐ฒ๐ฟ๐ฎ๐๐ฒ๐ฑ ๐๐บ๐ฎ๐ด๐ฒ๐ @mohammadasim98.bsky.social @wimmerthomas.bsky.social @mpi-inf.mpg.de @cvml.mpi-inf.mpg.de