SOAR: Advancements in Small Body Object Detection for Aerial Imagery Using State Space Models and Programmable Gradients

arXiv:2405.01699v1 Announce Type: new
Abstract: Small object detection in aerial imagery presents significant challenges in computer vision due to the minimal data inherent in small-sized objects and their propensity to be obscured by larger objects and background noise. Traditional methods using transformer-based models often face limitations stemming from the lack of specialized databases, which adversely affect their performance with objects of varying orientations and scales. This underscores the need for more adaptable, lightweight models. In response, this paper introduces two …

abstract aerial arxiv challenges computer computer vision cs.ai cs.cv data detection noise object objects small soar space state state space models transformer transformer-based models type vision