Jakub Gregorek

Big Marigold update!
Last year, we showed how to turn Stable Diffusion 2 into a SOTA depth estimator with a few synthetic samples and 2–3 days on just 1 GPU.
Today's release features:
🏎️ 1-step inference
🔢 New modalities
🫣 High resolution
🧨 Diffusers support
🕹️ New demos
🧶👇

Are you interested in joining our group? 🔥🚀

Postdoc in Autonomous Robots and Perception for Protein Design Laboratories - DTU Electro As part of a joint research collaboration between DTU and Novo Nordisk, we are looking for a postdoc to join our multidisciplinary research program focusing on the interplay between AI-Protein design,...

I am hiring a Postdoctoral Researcher to work on Computer Vision for Autonomous Robots in Life Science Automation.

#ComputerVision #Robotics #LabAutomation

Apply here: efzu.fa.em2.oraclecloud.com/hcmUI/Candid...

MDEC Challenge update! The 4th Monocular Depth Estimation Workshop at #CVPR2025 will be accepting submissions in two phases:
🚀 Dev phase: Feb 1 - Mar 1
🎯 Final phase: Mar 1 - Mar 21
Website: jspenmar.github.io/MDEC/
🌐 Codalab: codalab.lisn.upsaclay.fr/competitions...

Bring your best depth!

Join me at IEEE ICRA 2025 from 19-23 May 2025 in Atlanta, Georgia! Learn more

🚀 Our depth completion method SteeredMarigold will be presented at #ICRA2025 🚀. Meet @lanalpa.bsky.social and me in Atlanta between 19-23 May! invt.io/1exb0qqtfdj #robotics #depthcompletion #depthestimation

🌟 Exciting News! 🌟 We're thrilled to announce the launch of our website for SteeredMarigold 🚀 steeredmarigold.github.io. Our cutting-edge method helps to overcome limitations of depth sensors by completing missing areas in the depth maps 🤖. The code is coming! #DepthCompletion #DepthEstimation

A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor Fusion Model compression is essential in the deployment of large Computer Vision models on embedded devices. However, static optimization techniques (e.g. pruning, quantization, etc.) neglect the fact that d...

Our paper “A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor Fusion" is out as preprint!

By myself, @sscardapane.bsky.social, @rgring.bsky.social and @lanalpa.bsky.social

📄 arxiv.org/abs/2501.07451

Anyone interested in dynamic neural networks? 🧐

Introducing ⇆ Marigold-DC — our training-free zero-shot approach to monocular Depth Completion with guided diffusion! If you have ever wondered how else a long denoising diffusion schedule can be useful, we have an answer for you! Details 🧵

🔥🔥🔥

The Marigold paper has been an absolute inspiration. We can't wait for the arXiv release!