Robin Schön
YOU?
Author Swipe
View article: One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences
One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences Open
Understanding causality in event sequences with thousands of sparse event types is critical in domains such as healthcare, cybersecurity, or vehicle diagnostics, yet current methods fail to scale. We present OSCAR, a one-shot causal autore…
View article: MMMS: Multi-Modal Multi-Surface Interactive Segmentation
MMMS: Multi-Modal Multi-Surface Interactive Segmentation Open
In this paper, we present a method to interactively create segmentation masks on the basis of user clicks. We pay particular attention to the segmentation of multiple surfaces that are simultaneously present in the same image. Since these …
View article: CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations Open
2D scene graphs provide a structural and explainable framework for scene understanding. However, current work still struggles with the lack of accurate scene graph data. To overcome this data bottleneck, we present CoPa-SG, a synthetic sce…
View article: Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer
Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer Open
Analyzing a player's technique in table tennis requires knowledge of the ball's 3D trajectory and spin. While, the spin is not directly observable in standard broadcasting videos, we show that it can be inferred from the ball's trajectory …
View article: Efficient 2D to Full 3D Human Pose Uplifting including Joint Rotations
Efficient 2D to Full 3D Human Pose Uplifting including Joint Rotations Open
In sports analytics, accurately capturing both the 3D locations and rotations of body joints is essential for understanding an athlete's biomechanics. While Human Mesh Recovery (HMR) models can estimate joint rotations, they often exhibit …
View article: Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach Open
In this paper, we draw an analogy between processing natural languages and processing multivariate event streams from vehicles in order to predict when and what error pattern is most likely to occur in the future for a given car. Our appro…
View article: SkipClick: Combining Quick Responses and Low-Level Features for Interactive Segmentation in Winter Sports Contexts
SkipClick: Combining Quick Responses and Low-Level Features for Interactive Segmentation in Winter Sports Contexts Open
In this paper, we present a novel architecture for interactive segmentation in winter sports contexts. The field of interactive segmentation deals with the prediction of high-quality segmentation masks by informing the network about the ob…
View article: Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach Open
In this paper, we draw an analogy between processing natural languages and processing multivariate event streams from vehicles in order to predict $\textit{when}$ and $\textit{what}$ error pattern is most likely to occur in the future for …
View article: WSESeg: Introducing a Dataset for the Segmentation of Winter Sports Equipment with a Baseline for Interactive Segmentation
WSESeg: Introducing a Dataset for the Segmentation of Winter Sports Equipment with a Baseline for Interactive Segmentation Open
In this paper we introduce a new dataset containing instance segmentation masks for ten different categories of winter sports equipment, called WSESeg (Winter Sports Equipment Segmentation). Furthermore, we carry out interactive segmentati…
View article: Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation
Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation Open
Utilizing transformer architectures for semantic segmentation of high-resolution images is hindered by the attention's quadratic computational complexity in the number of tokens. A solution to this challenge involves decreasing the number …
View article: A Review and Efficient Implementation of Scene Graph Generation Metrics
A Review and Efficient Implementation of Scene Graph Generation Metrics Open
Scene graph generation has emerged as a prominent research field in computer vision, witnessing significant advancements in the recent years. However, despite these strides, precise and thorough definitions for the metrics used to evaluate…
View article: Adapting the Segment Anything Model During Usage in Novel Situations
Adapting the Segment Anything Model During Usage in Novel Situations Open
The interactive segmentation task consists in the creation of object segmentation masks based on user interactions. The most common way to guide a model towards producing a correct segmentation consists in clicks on the object and backgrou…
View article: The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data Open
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions r…
View article: All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes
All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes Open
Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines. In individual sports, these analyses mainly comprise the body posture. This paper focuses on the disciplines of triple, high, and …
View article: Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance Open
Pseudo depth maps are depth map predicitions which are used as ground truth during training. In this paper we leverage pseudo depth maps in order to segment objects of classes that have never been seen during training. This renders our obj…
View article: All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes
All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes Open
Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines. In individual sports, these analyses mainly comprise the body posture. This paper focuses on the disciplines of triple, high, and …
View article: Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation
Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation Open
Semi-supervised learning (SSL) can reduce the need for large labelled datasets by incorporating unlabelled data into the training. This is particularly interesting for semantic segmentation, where labelling data is very costly and time-con…
View article: COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings
COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings Open
Since COVID strongly affects the respiratory system, lung CT-scans can be used for the analysis of a patients health. We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection us…
View article: Unsupervised Domain Extension for Nighttime Semantic Segmentation in Urban Scenes
Unsupervised Domain Extension for Nighttime Semantic Segmentation in Urban Scenes Open
This paper deals with the problem of semantic image segmentation of street scenes at night, as the recent advances in semantic image segmentation are mainly related to daytime images. We propose a method to extend the learned domain of day…