activity
20182024
most citedLocalizing Small Apples in Complex Apple Orchard Environments

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

collaborators

6 papers

cs.CV2024

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…

cs.CV20221 cited

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…

cs.CV20222 cited

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2018

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…