collaborators

8 papers

cs.CV2026

LeAD-M3D: Leveraging Asymmetric Distillation for Real-Time Monocular 3D Detection

Johannes Meier, Jonathan Michel, Oussema Dhaouadi +7

Real-time monocular 3D object detection remains challenging due to severe depth ambiguity, viewpoint shifts, and the high computational cost of 3D reasoning. Existing approaches ei…

cs.CV2025

IDEAL-M3D: Instance Diversity-Enriched Active Learning for Monocular 3D Detection

Johannes Meier, Florian Günther, Riccardo Marin +3

Monocular 3D detection relies on just a single camera and is therefore easy to deploy. Yet, achieving reliable 3D understanding from monocular images requires substantial annotatio…

cs.CV2025

GrounDiff: Diffusion-Based Ground Surface Generation from Digital Surface Models

Oussema Dhaouadi, Johannes Meier, Jacques Kaiser +1

Digital Terrain Models (DTMs) represent the bare-earth elevation and are important in numerous geospatial applications. Such data models cannot be directly measured by sensors and…

cs.CV2025

OrthoLoC: UAV 6-DoF Localization and Calibration Using Orthographic Geodata

Oussema Dhaouadi, Riccardo Marin, Johannes Meier +2

Accurate visual localization from aerial views is a fundamental problem with applications in mapping, large-area inspection, and search-and-rescue operations. In many scenarios, th…

cs.CV2025

Highly Accurate and Diverse Traffic Data: The DeepScenario Open 3D Dataset

Oussema Dhaouadi, Johannes Meier, Luca Wahl +7

Accurate 3D trajectory data is crucial for advancing autonomous driving. Yet, traditional datasets are usually captured by fixed sensors mounted on a car and are susceptible to occ…

cs.CV2025

CoProU-VO: Combining Projected Uncertainty for End-to-End Unsupervised Monocular Visual Odometry

Jingchao Xie, Oussema Dhaouadi, Weirong Chen +3

Visual Odometry (VO) is fundamental to autonomous navigation, robotics, and augmented reality, with unsupervised approaches eliminating the need for expensive ground-truth labels.…