no code implementations • 4 Apr 2024 • Yuchen Liu, Luigi Palmieri, Sebastian Koch, Ilche Georgievski, Marco Aiello
Recent advancements in Large Language Models (LLMs) have sparked a revolution across various research fields.
no code implementations • 19 Feb 2024 • Sebastian Koch, Narunas Vaskevicius, Mirco Colosi, Pedro Hermosilla, Timo Ropinski
We co-embed the features from a 3D scene graph prediction backbone with the feature space of powerful open world 2D vision language foundation models.
no code implementations • 25 Oct 2023 • Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski
While it is widely accepted that pre-training is an effective approach to improve model performance in low data regimes, in this paper, we find that existing pre-training methods are ill-suited for 3D scene graphs.
no code implementations • 27 Sep 2023 • Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski
In the field of 3D scene understanding, 3D scene graphs have emerged as a new scene representation that combines geometric and semantic information about objects and their relationships.
1 code implementation • 1 Jul 2023 • Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann
Detecting objects and estimating their 6D poses is essential for automated systems to interact safely with the environment.
1 code implementation • 1 Dec 2022 • Sebastian Koch, Stefan Pasch
This paper introduces transformer-based language models to the literature measuring corporate culture from text documents.
Cultural Vocal Bursts Intensity Prediction text-classification +1
1 code implementation • 1 Mar 2022 • Leon Amadeus Varga, Sebastian Koch, Andreas Zell
We show that not all parameters have an equal impact on detection accuracy and data throughput, and that by using a suitable compromise between parameters we are able to achieve higher detection accuracy for lightweight object detection models, while keeping the same data throughput.
3 code implementations • CVPR 2019 • Sebastian Koch, Albert Matveev, Zhongshi Jiang, Francis Williams, Alexey Artemov, Evgeny Burnaev, Marc Alexa, Denis Zorin, Daniele Panozzo
We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD) models for research of geometric deep learning methods and applications.