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Matthias Rottmann

7 papers hereh-index 332 citations7 works total

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

author position
  • middle author1
  • last author6

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • math.NA1
same name
  • Matthias Rottmann — 11 papers, h 2
  • Matthias Rottmann — 5 papers, h 1
  • Matthias Rottmann — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedSparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data

3 citations · 4 across the 6 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

Unveiling Ontological Commitment in Multi-Modal Foundation Models

Mert Keser, Gesina Schwalbe, Niki Amini-Naieni +2

Ontological commitment, i.e., used concepts, relations, and assumptions, are a corner stone of qualitative reasoning (QR) models. The state-of-the-art for processing raw inputs, th…

cs.CV2024

On the Potential of Open-Vocabulary Models for Object Detection in Unusual Street Scenes

Sadia Ilyas, Ido Freeman, Matthias Rottmann

Out-of-distribution (OOD) object detection is a critical task focused on detecting objects that originate from a data distribution different from that of the training data. In this…

cs.CV2024★ 3 cited

SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data

Jialong Wu, Mirko Meuter, Markus Schoeler +1

Radar-based perception has gained increasing attention in autonomous driving, yet the inherent sparsity of radars poses challenges. Radar raw data often contains excessive noise, w…

cs.CV2024★ 1 cited

OoDIS: Anomaly Instance Segmentation and Detection Benchmark

Alexey Nekrasov, Rui Zhou, Miriam Ackermann +3

Safe navigation of self-driving cars and robots requires a precise understanding of their environment. Training data for perception systems cannot cover the wide variety of objects…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.