2 citations · 4 across the 12 of their papers we have counts for
14 papers
SegSLR: Promptable Video Segmentation for Isolated Sign Language Recognition
Sven Schreiber, Noha Sarhan, Simone Frintrop +1
Isolated Sign Language Recognition (ISLR) approaches primarily rely on RGB data or signer pose information. However, combining these modalities often results in the loss of crucial…
TRUDI and TITUS: A Multi-Perspective Dataset and A Three-Stage Recognition System for Transportation Unit Identification
Emre Gülsoylu, André Kelm, Lennart Bengtson +5
Identifying transportation units (TUs) is essential for improving the efficiency of port logistics. However, progress in this field has been hindered by the lack of publicly availa…
ContextLoss: Context Information for Topology-Preserving Segmentation
Benedict Schacht, Imke Greving, Simone Frintrop +2
In image segmentation, preserving the topology of segmented structures like vessels, membranes, or roads is crucial. For instance, topological errors on road networks can significa…
SOS: Segment Object System for Open-World Instance Segmentation With Object Priors
Christian Wilms, Tim Rolff, Maris Hillemann +2
We propose an approach for Open-World Instance Segmentation (OWIS), a task that aims to segment arbitrary unknown objects in images by generalizing from a limited set of annotated…
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection
Mykhailo Koshil, Tilman Wegener, Detlef Mentrup +2
Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an im…
Select High-Level Features: Efficient Experts from a Hierarchical Classification Network
André Kelm, Niels Hannemann, Bruno Heberle +5
This study introduces a novel expert generation method that dynamically reduces task and computational complexity without compromising predictive performance. It is based on a new…
SAD: Semi-supervised Small Apple Detection in Orchard Environments
Robert Johanson, Christian Wilms, Ole Johannsen +1
Crop detection is integral for precision agriculture applications such as automated yield estimation or fruit picking. However, crop detection, e.g., apple detection in orchard env…
High-Level Parallelism and Nested Features for Dynamic Inference Cost and Top-Down Attention
André Peter Kelm, Niels Hannemann, Bruno Heberle +5
This paper introduces a novel network topology that seamlessly integrates dynamic inference cost with a top-down attention mechanism, addressing two significant gaps in traditional…
Small, but important: Traffic light proposals for detecting small traffic lights and beyond
Tom Sanitz, Christian Wilms, Simone Frintrop
Traffic light detection is a challenging problem in the context of self-driving cars and driver assistance systems. While most existing systems produce good results on large traffi…
Segmenting Medical Instruments in Minimally Invasive Surgeries using AttentionMask
Christian Wilms, Alexander Michael Gerlach, Rüdiger Schmitz +1
Precisely locating and segmenting medical instruments in images of minimally invasive surgeries, medical instrument segmentation, is an essential first step for several tasks in me…
Localizing Small Apples in Complex Apple Orchard Environments
Christian Wilms, Robert Johanson, Simone Frintrop
The localization of fruits is an essential first step in automated agricultural pipelines for yield estimation or fruit picking. One example of this is the localization of apples i…
DeepFH Segmentations for Superpixel-based Object Proposal Refinement
Christian Wilms, Simone Frintrop
Class-agnostic object proposal generation is an important first step in many object detection pipelines. However, object proposals of modern systems are rather inaccurate in terms…
Superpixel-based Refinement for Object Proposal Generation
Christian Wilms, Simone Frintrop
Precise segmentation of objects is an important problem in tasks like class-agnostic object proposal generation or instance segmentation. Deep learning-based systems usually genera…
AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects
Christian Wilms, Simone Frintrop
We propose a novel approach for class-agnostic object proposal generation, which is efficient and especially well-suited to detect small objects. Efficiency is achieved by scale-sp…