Search Results for author: Jonas Schult

Found 10 papers, 5 papers with code

ControlRoom3D: Room Generation using Semantic Proxy Rooms

no code implementations8 Dec 2023 Jonas Schult, Sam Tsai, Lukas Höllein, Bichen Wu, Jialiang Wang, Chih-Yao Ma, Kunpeng Li, Xiaofang Wang, Felix Wimbauer, Zijian He, Peizhao Zhang, Bastian Leibe, Peter Vajda, Ji Hou

Central to our approach is a user-defined 3D semantic proxy room that outlines a rough room layout based on semantic bounding boxes and a textual description of the overall room style.

AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation

no code implementations1 Jun 2023 Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, Theodora Kontogianni

In an iterative process, the model assigns each data point to an object (or the background), while the user corrects errors in the resulting segmentation and feeds them back into the model.

Binary Classification Interactive Segmentation +2

Point2Vec for Self-Supervised Representation Learning on Point Clouds

1 code implementation29 Mar 2023 Karim Abou Zeid, Jonas Schult, Alexander Hermans, Bastian Leibe

Recently, the self-supervised learning framework data2vec has shown inspiring performance for various modalities using a masked student-teacher approach.

3D Part Segmentation Few-Shot 3D Point Cloud Classification +3

Mask3D: Mask Transformer for 3D Semantic Instance Segmentation

1 code implementation6 Oct 2022 Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany, Siyu Tang, Bastian Leibe

Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques.

3D Instance Segmentation 3D Semantic Instance Segmentation +1

Mix3D: Out-of-Context Data Augmentation for 3D Scenes

3 code implementations5 Oct 2021 Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, Francis Engelmann

Since scene context helps reasoning about object semantics, current works focus on models with large capacity and receptive fields that can fully capture the global context of an input 3D scene.

3D Semantic Segmentation

Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds

no code implementations2 Oct 2018 Francis Engelmann, Theodora Kontogianni, Jonas Schult, Bastian Leibe

In this paper, we present a deep learning architecture which addresses the problem of 3D semantic segmentation of unstructured point clouds.

3D Semantic Segmentation Segmentation

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