F. Güney

@fguney.bsky.social

research on computer vision, teaching, and movies. tweets in TR, EN

Sadra released the code for WarpRF 🚀 a training-free uncertainty quantification framework for radiance fields based on multi-view consistency, without training or any changes to the model.

https://github.com/sadrasafa/WarpRF

planning to visit Zurich on March 6. let me know if you would like to grab a coffee. I will try to convince robotics researchers that they still need computer vision at the Robotics, Vision, and Controls Talks at ETH Zurich 😄

while preparing for my ERC interview, I worked with a Turkish designer on my slides. I loved his work so much that I recommended him to friends, who recommended him to others, and so on. today he told me he’s been hired for 4 more projects. your work really does become your reference 😇

do I have any followers* here who happen to be ELLIS program/unit directors? to become an ELLIS scholar, I need their help with the nomination 🥰 *initially I said friends but then couldn’t stop laughing at the idea of me having friends who happen to be directors 😂

do you also feel bad when you realize you’re not only good at non-research tasks, but actually enjoy them? like… I shouldn’t like report-writing. I should be writing papers. and yet, talking about our achievements in the first ERC reporting period feels so good!

“Unlike a camera, which stores with equal resolution each bit of visual information, sight is highly directed. It is focused on capturing relevant information to convey meaning, not fidelity. …

The 4th AI for Robotics workshop surfaced converging themes around embodied perception, task learning & evaluation methodologies - emphasising a shift to integrated, context-aware systems. Dive into our key takeaways #AI #Robotics #spatialAI 🥽 ➡️ tinyurl.com/bvxxcn5e

Read about the 5 common themes that emerged from the talks and discussions at the 4th edition of this international workshop.

Common themes that emerged from the talks and discussions at the 4th edition of this international workshop.

tinyurl.com

last year after ECCV in Milano I joked about how expensive Italy felt and a few ppl kindly suggested I explore other parts of the country, so here I am taking the advice!

just wanted to clarify that we always try to report results (for sure for main results, maybe not all ablations) over 3 runs* for online evaluations as mean and std. maybe it was a mistake to show barplots without mentioning this. *probably not enough but still better than reporting only one run.

EuroHPC wrote a piece about our love of GPUs 😊 A EuroHPC Success Story | Clear Vision for Self-Driving Cars www.eurohpc-ju.europa.eu/eurohpc-succ...

A EuroHPC Success Story | Clear Vision for Self-Driving Cars

This Success Story highlights research developed by Dr Fatma Güney and her team using EuroHPC JU supercomputing resources. Their work, in the field of computer vision, addresses some of the remaining ...

eurohpc-ju.europa.eu

EuroHPC Joint Undertaking@eurohpc-ju.bsky.social · 10mo ago

Do #supercomputers impact your daily life? 🤔Dr @fguney.bsky.social's team at Koç University uses #EuroHPC’s #LEONARDO supercomputer to teach #cars to see and understand the world ⚡ Speeding up #AI models 🧐 Tracking real-world scenes A step closer to safer, smarter self-driving👉 link.europa.eu/YXGKR8

agreed. one of the messages from his talk is studying statistics, computer science, and economics together. I find his perspective on AI very realistic. also, how he changed the direction of discussion on bias during the panel in the end, should be studied in textbooks.

Eugene Vinitsky 🍒@eugenevinitsky.bsky.social · 2y ago

Michael Jordan's talk on the multi-agent and micro-econ perspective on AI and how we need a new vision of the future is killer: www.youtube.com/live/W0QLq4q...

in a privileged setting, RL with self-play seems to be the answer to planning for driving. impressive to see complex behavior learning without supervision and zero-shot generalization across benchmarks by GigaFlow. the next question is what about with perception, is it just a matter of computation?

open-source, open-weight, I'll take whichever because, unlike the ones who share nothing, a few at least make an effort and change the game for everyone. I expect the effect of open stuff like Cosmos to be huge on physical AI. we are already trying it. also downloaded the DeepSeek, we shall see 🤞