Search Results for author: Sebastian Koch

Found 7 papers, 4 papers with code

Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships

no code implementations19 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.

Object

Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction

no code implementations25 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.

Language Modelling

SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction

no code implementations27 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.

Graph Learning Scene Understanding

CultureBERT: Measuring Corporate Culture With Transformer-Based Language Models

1 code implementation1 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

Comprehensive Analysis of the Object Detection Pipeline on UAVs

1 code implementation1 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.

Camera Calibration Object +3

ABC: A Big CAD Model Dataset For Geometric Deep Learning

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.

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