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Posts by Andreea Ardelean

Very proud of Paul who got his master thesis at @fau.de accepted at @cvprconference.bsky.social - the most impactful conference!

Joint supervision with @andreead-a.bsky.social , @jadgardner.bsky.social and @willsmithvision.bsky.social

2 months ago 7 2 0 0
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At SIGGRAPH Asia in December, I presented our latest work on generating arbitrarily large, tileable textures with irregular features, developed together with @timweyrich.bsky.social.
🎨 Today I am excited to announce we added a Blender plugin to our official code release: github.com/TArdelean/Fe... πŸ˜„

2 months ago 2 2 1 0
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Had a great experience presenting our work on 3D scene reconstruction from a single image with @visionbernie.bsky.social at #3DV2025 πŸ‡ΈπŸ‡¬

andreeadogaru.github.io/Gen3DSR

Reach out if you're interested in discussing our research or exploring international postdoc opportunities @fau.de

1 year ago 18 4 0 2
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Scanning Electron Microscopes analyze invisible surfaces. However, they’re only able to take grayscale images. Manual coloring is a cumbersome process and that’s why FAU researchers are using the 3D structure to propagate one colorized view to a whole scene. Impressive! 🎨

Artwork by Micronaut.

1 year ago 21 4 1 0

Work with @mert-o.bsky.social and @visionbernie.bsky.social at @cogcovi.bsky.social @unifau.bsky.social, where we have two year fully-funded postdoc positions open on related topics. (5/5)

1 year ago 4 0 0 0
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We handle occlusions by employing amodal completion for each instance. The completed instance is then reconstructed using existing models that perform well for single objects. However, we first address the object crop domain shift (e.g., focal length) through reprojection. (4/5)

1 year ago 3 1 1 0
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First, we parse the image of the scene by identifying the composing entities and estimating the depth and camera parameters. Each instance is then processed individually. The unprojected depth serves as a layout reference for composing the scene in 3D space. (3/5)

1 year ago 3 1 1 0

Most single-image scene-level reconstruction methods require 3D supervised end-to-end training and suffer from poor generalization capabilities. We propose a modular approach where each component performs well by focusing on specific tasks that are easier to supervise. (2/5)

1 year ago 2 1 1 0
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Excited to share our paper which will be presented at #3DV2025

✨ Gen3DSR: Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View ✨
🌐 Project page: andreeadogaru.github.io/Gen3DSR
πŸ“„ Paper: arxiv.org/abs/2404.03421
πŸ‘©β€πŸ’» Code: github.com/AndreeaDogar...
(1/5)

1 year ago 23 6 1 0
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