Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning

no code implementations • 17 Jul 2023 • Aral Hekimoglu, Michael Schmidt, Alvaro Marcos-Ramiro

We propose a novel semi-supervised active learning (SSAL) framework for monocular 3D object detection with LiDAR guidance (MonoLiG), which leverages all modalities of collected data during model development.

Active Learning Monocular 3D Object Detection +1

Active Learning for Object Detection with Non-Redundant Informative Sampling

no code implementations • 17 Jul 2023 • Aral Hekimoglu, Adrian Brucker, Alper Kagan Kayali, Michael Schmidt, Alvaro Marcos-Ramiro

Curating an informative and representative dataset is essential for enhancing the performance of 2D object detectors.

Active Learning Image Classification +4

Multi-Task Consistency for Active Learning

no code implementations • 21 Jun 2023 • Aral Hekimoglu, Philipp Friedrich, Walter Zimmer, Michael Schmidt, Alvaro Marcos-Ramiro, Alois C. Knoll

In single-task vision-based settings, inconsistency-based active learning has proven to be effective in selecting informative samples for annotation.

Active Learning object-detection +2