activity
20202026
most citedMuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop

5 citations · 9 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Autonomous Structuring of Radiology Reports Across Modalities at Archive Scale Using an Open-Weight Large Language Model

Friedrich Puttkammer, Fabian Drexel, Marlene Fritzsche +19

Purpose: To develop and evaluate an open-weight large language model (LLM) pipeline that converts an entire archive of free-text radiology reports into structured reports without h…

cs.CV2026

RadPRISM: Schema-stratified radiology-report supervision for concept-disentangled image representations and visual grounding

Fabian Drexel, Marlene Fritzsche, Era Stambollxhiu +15

Vision-language pretraining learns rich medical image representations from radiology reports, but previous model variants commonly operate within a single shared embedding space, s…

cs.CV2021

A Physiologically-Adapted Gold Standard for Arousal during Stress

Alice Baird, Lukas Stappen, Lukas Christ +3

Emotion is an inherently subjective psychophysiological human-state and to produce an agreed-upon representation (gold standard) for continuous emotion requires a time-consuming an…

cs.CL2021★ 1 cited

MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox

Lukas Stappen, Lea Schumann, Benjamin Sertolli +4

We introduce the MuSe-Toolbox - a Python-based open-source toolkit for creating a variety of continuous and discrete emotion gold standards. In a single framework, we unify a wide…

cs.CL2021★ 1 cited

The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress

Lukas Stappen, Alice Baird, Lukas Christ +6

Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of sentiment and emotion, as well as physiological-emotion and emotion-based stress recognition throu…

cs.MM2021★ 2 cited

The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements

Lukas Stappen, Alice Baird, Lea Schumann +1

Truly real-life data presents a strong, but exciting challenge for sentiment and emotion research. The high variety of possible `in-the-wild' properties makes large datasets such a…

cs.MM2020★ 5 cited

MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop

Lukas Stappen, Alice Baird, Georgios Rizos +9

Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 is a Challenge-based Workshop focusing on the tasks of sentiment recognition, as well as emotion-target engagement and…