28 citations · 53 across the 16 of their papers we have counts for
18 papers
The Failure Is in the Readout: Fine-Grained Emotion Recognition Benchmarks Measure Elicitation, Not Perception
Tobias Hallmen, Fabian Deuser, Robin-Nico Kampa +2
Fine-grained emotion recognition supports therapy tools and social robots, but it needs facial data, which raises privacy and data-protection concerns. EmoNet-Face-HQ answers that…
Managing Action Preconditions in Neuro-Symbolic RL: Three Placement Strategies for Embodied Agents
Norbert Oswald, Fabian Deuser, Thomas Bräunl
Humans carry behaviour knowledge of how to act in familiar situations into every new task rather than relearning it from scratch. There is no reason a Reinforcement Learning (RL) a…
1GC-7RC: One Graphic Card -- Seven Research Challenges! How Good Are AI Agents at Doing Your Job?
Robin-Nico Kampa, Fabian Deuser, Anna Bößendörfer +2
Autonomous AI coding agents are becoming a core tool for ML practitioners in industry and research alike. Despite this growing adoption, no standardized benchmark exists to evaluat…
ViewSparsifier: Killing Redundancy in Multi-View Plant Phenotyping
Robin-Nico Kampa, Fabian Deuser, Konrad Habel +1
Plant phenotyping involves analyzing observable characteristics of plants to better understand their growth, health, and development. In the context of deep learning, this analysis…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
synth-dacl: Does Synthetic Defect Data Enhance Segmentation Accuracy and Robustness for Real-World Bridge Inspections?
Johannes Flotzinger, Fabian Deuser, Achref Jaziri +4
Adequate bridge inspection is increasingly challenging in many countries due to growing ailing stocks, compounded with a lack of staff and financial resources. Automating the key t…
Locality-Sensitive Hashing for Efficient Hard Negative Sampling in Contrastive Learning
Fabian Deuser, Philipp Hausenblas, Hannah Schieber +3
Contrastive learning is a representational learning paradigm in which a neural network maps data elements to feature vectors. It improves the feature space by forming lots with an…
Semantic Matters: Multimodal Features for Affective Analysis
Tobias Hallmen, Robin-Nico Kampa, Fabian Deuser +2
In this study, we present our methodology for two tasks: the Emotional Mimicry Intensity (EMI) Estimation Challenge and the Behavioural Ambivalence/Hesitancy (BAH) Recognition Chal…
SoccerNet 2024 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +81
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…
Unimodal Multi-Task Fusion for Emotional Mimicry Intensity Prediction
Tobias Hallmen, Fabian Deuser, Norbert Oswald +1
In this research, we introduce a novel methodology for assessing Emotional Mimicry Intensity (EMI) as part of the 6th Workshop and Competition on Affective Behavior Analysis in-the…
SoccerNet 2023 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +99
The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…
dacl1k: Real-World Bridge Damage Dataset Putting Open-Source Data to the Test
Johannes Flotzinger, Philipp J. Rösch, Norbert Oswald +1
Recognising reinforced concrete defects (RCDs) is a crucial element for determining the structural integrity, traffic safety and durability of bridges. However, most of the existin…
Orientation-Guided Contrastive Learning for UAV-View Geo-Localisation
Fabian Deuser, Konrad Habel, Martin Werner +1
Retrieving relevant multimedia content is one of the main problems in a world that is increasingly data-driven. With the proliferation of drones, high quality aerial footage is now…
CLIP-ReIdent: Contrastive Training for Player Re-Identification
Konrad Habel, Fabian Deuser, Norbert Oswald
Sports analytics benefits from recent advances in machine learning providing a competitive advantage for teams or individuals. One important task in this context is the performance…
Sample4Geo: Hard Negative Sampling For Cross-View Geo-Localisation
Fabian Deuser, Konrad Habel, Norbert Oswald
Cross-View Geo-Localisation is still a challenging task where additional modules, specific pre-processing or zooming strategies are necessary to determine accurate positions of ima…
NeRFtrinsic Four: An End-To-End Trainable NeRF Jointly Optimizing Diverse Intrinsic and Extrinsic Camera Parameters
Hannah Schieber, Fabian Deuser, Bernhard Egger +2
Novel view synthesis using neural radiance fields (NeRF) is the state-of-the-art technique for generating high-quality images from novel viewpoints. Existing methods require a prio…
Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model
Fabian Deuser, Konrad Habel, Philipp J. Rösch +1
Current architectures for multi-modality tasks such as visual question answering suffer from their high complexity. As a result, these architectures are difficult to train and requ…
Building Inspection Toolkit: Unified Evaluation and Strong Baselines for Damage Recognition
Johannes Flotzinger, Philipp J. Rösch, Norbert Oswald +1
In recent years, several companies and researchers have started to tackle the problem of damage recognition within the scope of automated inspection of built structures. While comp…