What do you see in these images? These are called hybrid images, originally proposed by Aude Oliva et al. They change appearance depending on size or viewing distance, and are just one kind of perceptual illusion that our method, Factorized Diffusion, can make.

ICVSS - Class 2024

The 1st workshop on “Explainable Computer Vision: Where are We and Where are We Going?” at #ECCV2024 is accepting submissions across topics in XAI in computer vision! The submission deadline for the proceedings track is July 24, 2024 23:59 CEST (in ~3 days!). European Conference on Computer Vision #ECCV2026 (1/3)

Share your latest published work for explainability in computer vision at our workshop at #ECCV2024! Submit to our Non-Proceedings track, deadline is tomorrow (Aug 5, 23:59 CEST)! Details: excv-workshop.github.io European Conference on Computer Vision #ECCV2026

Notifications of decisions have now been sent to authors of all submissions. Congratulations to all the authors whose papers were accepted, and a big thanks to all the reviewers! See you at the workshop! #ECCV2024 European Conference on Computer Vision #ECCV2026

🏔️🇨🇭"Grüezi" from our summer retreat in the Swiss mountains. It’s been a fantastic week filled with research discussions, hikes, and amazing Swiss food.

Less than three days to go for the eXCV Workshop at #ECCV2024! Join us on Sunday from 14:00-18:00 in Brown 1 to hear about the state of XAI research from an exciting lineup of speakers! Olga Russakovsky, Rene Vidal, Sunnie S. Y. Kim ☀️, Yossi Gandelsman, Zeynep Akata European Conference on Computer Vision #ECCV2026 (1/4)

Excited to give a talk about interpretability via reverse engineering tmrw at European Conference on Computer Vision #ECCV2026!

Thanks to all the speakers for the exciting talks and all the authors for their interesting posters! It was a pleasure to have such a great program.

This year's #ECCV2024 recap: Presented our work w Shashank Agnihotri on Uspampling ⬆️, our work on infinitely large convolutions ♾️ , went to the Doctoral Consortium 🎓 and met with new and old friends 🍻 thanks European Conference on Computer Vision #ECCV2026, it was a blast!

After mech int work on vision models and on language models, it’s time to see what’s going on inside VLMs! Not only that the logit lens on image features works, we show that these features can be linearly edited to reduce hallucinations! Nick Jiang and anish are great!

🎭Recent work shows that models’ inductive biases for 'simpler' features may lead to shortcut learning. What do 'simple' vs 'complex' features look like? What roles do they play in generalization? Our new paper explores these questions. arxiv.org/pdf/2407.06076 #Neurips2024

Our work on transforming existing neural networks to be inherently interpretable has been accepted at #NeurIPS2024! This is joint work with Shreyash Arya, Moritz Böhle, and Bernt Schiele at Computer Vision and Machine Learning - MPI-INF. (1/4)

📢 Excited to share our new work: AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers snap-research.github.io/ac3d We analyze what pre-trained video diffusion transformers understand about 3D and demonstrate dynamic scene generation with 3D control.

Want to learn about how model design choices affect the attribution quality of vision models? Visit our #NeurIPS2024 poster on Friday afternoon (East Exhibition Hall A-C #2910)! Robin Hesse Simone Schaub Stefan Roth Paper: arxiv.org/abs/2407.11910 Code: github.com/visinf/idsds

Got a strong XAI paper rejected from ICCV? Submit it to our ICCV eXCV Workshop today—we welcome high-quality work! 🗓️ Submissions open until June 26 AoE. 📄 Got accepted to ICCV? Congrats! Consider our non-proceedings track. #ICCV2025 #ICCV2025

Got questions about the state of explainable AI in computer vision? Drop them here, and our speakers might discuss them!