Joan Serrat — accepted AI-conference papers

2024

Implicit Learning of Scene Geometry From Poses for Global Localization

Mohammad Altillawi, Shile Li, Sai Manoj Prakhya, Ziyuan Liu, Joan Serrat

RA-L 2024

Global visual localization estimates the absolute pose of a camera using a single image, in a previously mapped area. Obtaining the pose from a single image enables many robotics and augmented/virtual reality applications. Inspired by latest advances in deep learning, many existing approaches direct

Cited by 3 Source ↗Scholar ↗

2020

Learning Multi-Object Tracking and Segmentation From Automatic Annotations

Lorenzo Porzi, Markus Hofinger, Idoia Ruiz, Joan Serrat, Samuel Rota Bulo, Peter Kontschieder

CVPR 2020poster

In this work we contribute a novel pipeline to automatically generate training data, and to improve over state-of-the-art multi-object tracking and segmentation (MOTS) methods. Our proposed track mining algorithm turns raw street-level videos into high-fidelity MOTS training data, is scalable and ov…

Cited by 96 PDF ↗code ↗Scholar ↗