We analyse the scene, detecting and tracking objects in 2D and 3D, with a focus on efficiency and on working under limited resources.
Methods: Efficient 2D and 3D object detection
Efficiently locating objects and tracking them across time is a fundamental task in autonomous agents navigation. We explore different directions both in 2D and 3D.
Collaboration with TUM
ReferencesMouawad I, Odone F. FasterVideo: Efficient Online Joint Object Detection And Tracking. To appear in ICIAPSpringer.
Mouawad I, Brasch N, Manhardt F, Tombari F, Odone F. Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection. arXiv preprint arXiv:2203.2022
Methods: Working in a limited resources regime
For 2D tasks, we study approaches to harness temporal prior essential for tracking, thus, performing joint detection and tracking while striking competitive speed-accuracy trade-off.
Applications: Marine robotics
While for 3D perception, where annotating objects with 3D cuboids is a costly and time consuming process, our aim is to investigate self-supervised pipelines, thus, unlocking the potential of widely-available raw data.
UniGe-Graal and ISME