PifPaf: Composite Fields for Human Pose Estimation

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

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This doctoral thesis navigates the complex landscape of motion coordination and formation control within teams of rotary-wing Micro Aerial Vehicles (MAVs). Prompted by the intricate demands of real-world applications such as search and rescue or surveillan ...

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where the collaborative efforts of "simple" individuals can lead to the emergence of complex dynamics. The reliance of each organism on the collective is so great t ...

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Modular robotics link the reliability of a centralised system with the adaptivity of a decentralised system. It is difficult for a robot with a fixed shape to be able to perform many different types of tasks. As the task space grows, the number of functi ...

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The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle t ...

Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...

Multimodal unmanned aerial vehicles (UAVs) are rarely capable of more than two modalities, i.e., flying and walking or flying and perching. However, being able to fly, perch, and walk could further improve their usefulness by expanding their operating enve ...

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PifPaf: Composite Fields for Human Pose Estimation

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Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance

Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

Distributed Predictive Formation Control of Autonomous Rotary-Wing Micro Aerial Vehicles

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Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Chaotic microcomb inertia-free parallel ranging

Haptics based multi-level collaborative steering control for automated driving

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

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MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency

Region Extraction in Mesh Intersection

Avian-Inspired Claws Enable Robot Perching or Walking

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Regularization of polynomial networks for image recognition