| Aug 27, 2025 |
🚨 Paper Announcement: Two papers accepted at ICCV 2025! 🎉 We’re thrilled to share that CAD-Assistant and CAD-Recode, our two recent papers on AI for Computer Aided Design (CAD) that are accepted at ICCV 2025 🚀.
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| Jun 10, 2025 |
🚀 Morfis at CVPR 2025. The Morfis Platform for AI-Assisted Physical Product Customization will be showcased at CVPR 2025 demo session.
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| Feb 03, 2025 |
Very exciting news, the Morfis project has been selected to be part of this years cohort of the Venture Program of SnT. Check out the project video here 🎥!
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| Dec 03, 2024 |
Paper announcement 📢📢 !!! Our work entitled DAVINCI: A Single-Stage Architecture for Constrained CAD Sketch Inference was presented as an oral 🎉🎉 at the British Machine Vision Conference (BMVC) 2024! For more details check out the project page.
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| Dec 01, 2024 |
Our recent work PICASSO: A Feed-Forward Framework for Parametric Inference of CAD Sketches via Rendering Self-Supervision has been accepted for publication at WACV 2025!
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| Oct 03, 2024 |
New Paper!!! Our work on TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds will be presented on ECCV 2024.
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| Dec 17, 2023 |
New Paper!!! Our work on Self-Supervised Learning for Visual Relationship Detection through Masked Bounding Box Reconstruction will be presented on WACV 2024.
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| Oct 01, 2023 |
Great news to share: Our paper on Interpretable Visual Question Answering Via Reasoning Supervision will be presented on ICIP 2023 as a lecture 🎉. Great work from Maria Parelli 🎉. Thanks to all authors, Markos Diomataris and Vassilis Pitsikalis and Deeplab for a great collaboration.
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| Sep 10, 2023 |
Happy to share that our paper entitled SHARP 2023 Challenge: Solving CAD History and pArameters Recovery from Point clouds and 3D scans. Overview, Datasets, Metrics, and Baselines will be presented at the SHARP2023 ICCV Workshop.
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| Apr 01, 2023 |
I have now started my new position as Postdoctoral Researcher at the SnT, Interdisciplinary Centre for Security, Reliability and Trust of the University of Luxembourg.
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| Jan 04, 2023 |
Our paper From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery has been accepted for publication at IEEE Transactions on Pattern Analysis and Machine Intelligence. The paper extends our NeurIPS 2020 work on unsupervised landmark discovery both conceptually and experimentally!
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