Supervised machine learning methods for image analysis require large amounts of labelled
training data to solve computer vision problems. The recent rise of deep learning algorithms …

This work proposes a novel pose estimation model for object categories that can be
effectively transferred to pre-viously unseen environments. The deep convolutional network …

Strong demand for autonomous vehicles and the wide availability of 3D sensors are
continuously fueling the proposal of novel methods for 3D object detection. In this paper, we …

The study of wildlife populations and species has gained increased relevance due to
significant endangerment, loss of habitats and world climate change. Using camera traps for …

Large-scale 3D point clouds are often used as training data for 3D semantic segmentation,
but the labor-intensive nature of the annotation process challenges the acquisition of …

The demand for high-quality annotated data has surged in recent years for applications
driven by real-world artificial intelligence, such as autonomous driving and embodied …

Large Language Models (LLMs) have achieved impressive progress in decision-making
and task automation for intelligent agents. However, multiple agents must cooperate to …

Computer-generated imagery of car models has become an indispensable part of car
manufacturers' advertisement concepts. They are for instance used in car configurators to …

Segmenting and determining the 3D bounding boxes of objects of interest in RGB videos is
an important task for a variety of applications such as augmented reality, navigation, and …

In 3D apple detection, the challenge of direction for apple stem harvesting for agricultural
robotics has not yet been resolved. Addressing the issue of determining the stem direction of …