Static neural networks are powerful, but the future of efficient AI lies in Dynamic Neural Networks (DyNNs)—models that adapt their structure or parameters during inference. 🏎️ ↔🐢

Where to Attend: A Principled Vision-Centric Position Encoding with Parabolas Paper: arxiv.org/abs/2602.01418 Website: chrisohrstrom.github.io/parabolic-po... Code: github.com/DTU-PAS/para... @rgring.bsky.social @lanalpa.bsky.social

Where to Attend: A Principled Vision-Centric Position Encoding with Parabolas

We propose Parabolic Position Encoding (PaPE), a parabola-based position encoding for vision modalities in attention-based architectures. Given a set of vision tokens-such as images, point clouds, vid...

arxiv.org

What if position encodings were designed for vision from scratch? We introduce PaPE—Parabolic Position Encoding. Outperforms RoPE on 7/8 datasets and extrapolates to higher resolutions without fine-tuning or position interpolation. Paper, code, and website in thread 🧵

Kudos to the authors: Junru Ren, Abhijoy Mandal, Rama El-khawaldeh, Shi Xuan Leong, @profhein.bsky.social, @aspuru.bsky.social, @lanalpa.bsky.social and Kourosh Darvish. [6/6]

This approach enables more reliable real-time monitoring for automated workflows such as liquid–liquid extraction, distillation, and crystallization—bringing us closer to truly adaptive, autonomous chemistry labs. [5/6]

Now in Digital Discovery: Context-aware computer vision for chemical reaction state detection. 🔗 pubs.rsc.org/en/content/a... [1/6]

Exciting new research from our group! 🦾🤓🎓

Christoffer Koo Øhrstrøm@chrisohrstrom.bsky.social · 9mo ago

What if we could represent events (event cameras) in a way that preserves both asynchrony and spatial sparsity? Exited to share our latest work where we answer this question positively. Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras Paper: arxiv.org/abs/2510.26614

Join us and revolutionize Life Science Lab Automation! 🎓🤖💉 I am hiring a Postdoc in Robotics and Computer Vision for Life Science Laboratory Automation, in Copenhagen, Denmark. Is that you? 🙋‍♀️ efzu.fa.em2.oraclecloud.com/hcmUI/Candid...

Postdoc in Robotics and Computer Vision for Life Science Laboratory Automation - 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,...

efzu.fa.em2.oraclecloud.com

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...

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,...

efzu.fa.em2.oraclecloud.com

📣NEW DATASET ALERT! 🧱🚧 We are happy to present our latest research work in @elsevierconnect.bsky.social "Automation in Construction" journal: doi.org/10.1016/j.au... a work driven by my PhD student, Patrick Schmidt! Find the corresponding repo here: github.com/DTU-PAS/ConR...

GitHub - DTU-PAS/ConRebSeg: ConRebSeg: A Segmentation Dataset for Reinforced Concrete Construction

ConRebSeg: A Segmentation Dataset for Reinforced Concrete Construction - DTU-PAS/ConRebSeg

github.com

Depth completion for real-world depth sensors? 🤖 Check out our latest work: steeredmarigold.github.io

Jakub Gregorek@jakubgregorek.bsky.social · 2y ago

🌟 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

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

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...

arxiv.org

Can Dynamic Neural Networks boost Computer Vision and Sensor Fusion? We are very happy to share this awesome collection of papers on the topic!

Fabio Montello@zioictus.bsky.social · 2y ago

First little project of the year: an awesome collection of papers on Dynamic Neural Networks for Computer Vision and Sensor Fusion! Each paper comes with a brief summary and code link. 👉 github.com/DTU-PAS/awes...

[Last Chance] Two more days before the DL for the Lecturer in Computer Vision Post @bristoluni.bsky.social [6 Jan DL] This is a great opportunity to establish your own research group in a supportive environment. Pls circulate and apply. www.jobs.ac.uk/job/DKR225/l...

Lecturer in Machine Learning & Computer Vision at University of Bristol

Recruiting now: Lecturer in Machine Learning & Computer Vision on jobs.ac.uk. Click for details and explore more academic job opportunities on the top job board

jobs.ac.uk

Dima Damen@dimadamen.bsky.social · 2y ago

Pls RT Permanent Assistant Professor (Lecturer) position in Computer Vision @bristoluni.bsky.social [DL 6 Jan 2025] This is a research+teaching permanent post within MaVi group uob-mavi.github.io in Computer Science. Suitable for strong postdocs or exceptional PhD graduates. t.co/k7sRRyfx9o 1/2

The academic journey is wonderful when you share it with a great team! 🎓 I am very proud of my 2 PhD students who graduated in 2024, Dimitrios Arapis (now with Novo Nordisk) and Ronja Güldenring (continuing with us in DTU Electro).

Computer Vision: Fact & Fiction is now available on YouTube 🙌🏼 I made a playlist for it with the seven chapters. Enjoy this time capsule from two decades ago!

Computer Vision: Fact & Fiction - YouTube

Title Computer Vision: Fact and Fiction Year of Publication 2005 Author(s) Marília Maschion Vincent Rabaud Serge Belongie URL https://vision.ucsd.edu/publica...

youtube.com

Serge Belongie@serge.belongie.com · 2y ago

In 2005 two UCSD students (Marília Maschion and Vincent Rabaud) and I made a documentary about the state-of-the-art in Computer Vision, based on interviews with researchers at CVPR in San Diego, CA (1/5)

Maybe this is it? arxiv.org/abs/2409.10202 @jakubgregorek.bsky.social

SteeredMarigold: Steering Diffusion Towards Depth Completion of Largely Incomplete Depth Maps

Even if the depth maps captured by RGB-D sensors deployed in real environments are often characterized by large areas missing valid depth measurements, the vast majority of depth completion methods st...

arxiv.org

Welcome @jflalonde.bsky.social! Your starter pack awaits 👇 go.bsky.app/M7HGC3Y

and this too 👇 go.bsky.app/Gjcs339

Super EXCITED to host @dimadamen.bsky.social here in #Toronto the next couple of days!