MOD-CL: Multi-label Object Detection with Constrained Loss

arXiv:2403.07885v1 Announce Type: new
Abstract: We introduce MOD-CL, a multi-label object detection framework that utilizes constrained loss in the training process to produce outputs that better satisfy the given requirements. In this paper, we use $\mathrm{MOD_{YOLO}}$, a multi-label object detection model built upon the state-of-the-art object detection model YOLOv8, which has been published in recent years. In Task 1, we introduce the Corrector Model and Blender Model, two new models that follow after the object detection process, aiming to generate …

abstract art arxiv cs.ai cs.cv detection framework loss object paper process requirements state training type yolo yolov8