I am a PhD student at the Visual Computing Lab with the focus on 3D scene understanding, representation & generation. I did my Master's Thesis in the same group about Transfer Learning between Synthetic and Real Data. This thesis concluded the Informatics: Games Engineering program (M.Sc) with specializations on Computer Graphics and Animation and Hardware-aware Programming. In 2015, I received my Bachelor's degree (B.Sc) Informatics: Games Engineering from the Technical University of Munich (TUM). From August 2016 until June 2017, I took part in the Erasmus mobility program, in which I was studying at Chalmers University of Technology, Sweden. In spring 2019, I spent three months at Stanford University visiting Geometric Computation group of Prof. Leonidas Guibas.
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|Panoptic 3D Scene Reconstruction From a Single RGB Image|
|Manuel Dahnert, Ji Hou, Matthias Nießner, Angela Dai|
|Panoptic 3D Scene Reconstruction combines the tasks of 3D reconstruction, semantic segmentation and instance segmentation. From a single RGB image we predict 2D information and lift these into a sparse volumetric 3D grid, where we predict geometry, semantic labels and 3D instance labels.|
|Joint Embedding of 3D Scan and CAD Objects|
|Manuel Dahnert, Angela Dai, Leonidas Guibas, Matthias Nießner|
|In this paper, we address the problem of cross-domain retrieval between partial, incomplete 3D scan objects and complete CAD models. To this end, we learn a joint embedding where semantically similar objects from both domains lie close together regardless of low-level differences, such as clutter or noise. To enable fine-grained evaluation of scan-CAD model retrieval we additionally present a new dataset of scan-CAD object similarity annotations.|
|Scan2CAD: Learning CAD Model Alignment in RGB-D Scans|
|Armen Avetisyan, Manuel Dahnert, Angela Dai, Angel X. Chang, Manolis Savva, Matthias Nießner|
|CVPR 2019 (Oral)|
|We present Scan2CAD, a novel data-driven method that learns to align clean 3D CAD models from a shape database to the noisy and incomplete geometry of a commodity RGB-D scan.|