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Dávid Rozenberszki

TUM 3D AI Lab

4 papers hereh-index 5484 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
affiliations
  • TUM 3D AI Lab

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2025

DCSEG: Decoupled 3D Open-Set Segmentation using Gaussian Splatting

Luis Wiedmann, Luca Wiehe, David Rozenberszki

Open-set 3D segmentation represents a major point of interest for multiple downstream robotics and augmented/virtual reality applications. We present a decoupled 3D segmentation pi…

cs.CV2025

ExCap3D: Expressive 3D Scene Understanding via Object Captioning with Varying Detail

Chandan Yeshwanth, David Rozenberszki, Angela Dai

Generating text descriptions of objects in 3D indoor scenes is an important building block of embodied understanding. Existing methods do this by describing objects at a single lev…

cs.CV2024

DiffCAD: Weakly-Supervised Probabilistic CAD Model Retrieval and Alignment from an RGB Image

Daoyi Gao, Dávid Rozenberszki, Stefan Leutenegger +1

Perceiving 3D structures from RGB images based on CAD model primitives can enable an effective, efficient 3D object-based representation of scenes. However, current approaches rely…

cs.CV2024

UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes

David Rozenberszki, Or Litany, Angela Dai

3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensiv…

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