3 citations · 4 across the 4 of their papers we have counts for
6 papers
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…
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…
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…
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…
Language-Grounded Indoor 3D Semantic Segmentation in the Wild
David Rozenberszki, Or Litany, Angela Dai
Recent advances in 3D semantic segmentation with deep neural networks have shown remarkable success, with rapid performance increase on available datasets. However, current 3D sema…
LOL: Lidar-Only Odometry and Localization in 3D Point Cloud Maps
David Rozenberszki, Andras Majdik
In this paper we deal with the problem of odometry and localization for Lidar-equipped vehicles driving in urban environments, where a premade target map exists to localize against…