Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances
Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep learning techniques have demonstrated robust feature representation capabilities and led to a big leap in the development of RSOD techniques. In this era of rapid technical evolution, this review aims to present a comprehensive review of the recent achievements in deep learning based RSOD methods. More than 300 papers are covered in this review. We identify five main challenges in RSOD, including multi-scale object detection, rotated object detection, weak object detection, tiny object detection, and object detection with limited supervision, and systematically review the corresponding methods developed in a hierarchical division manner. We also review the widely used benchmark datasets and evaluation metrics within the field of RSOD, as well as the application scenarios for RSOD. Future research directions are provided for further promoting the research in RSOD.
Code (0)
등록된 구현이 없습니다.
Tasks
Objectobject-detectionObject DetectionSimilar Papers 제목 키워드 기반
Few-shot Object Detection on Remote Sensing Images
In this paper, we deal with the problem of object detection on remote sensing images. Previous methods have developed numerous deep CNN-based methods for object detection on remote sensing images and the report remarkabl…
Few-Shot LearningFew-Shot Object DetectionObjectobject-detection+1Transformation-Invariant Network for Few-Shot Object Detection in Remote Sensing Images
Object detection in remote sensing images relies on a large amount of labeled data for training. However, the increasing number of new categories and class imbalance make exhaustive annotation impractical. Few-shot objec…
Few-Shot Object DetectionMeta-LearningObjectobject-detection+1A Light-Weight Object Detection Framework with FPA Module for Optical Remote Sensing Imagery
With the development of remote sensing technology, the acquisition of remote sensing images is easier and easier, which provides sufficient data resources for the task of detecting remote sensing objects. However, how to…
Objectobject-detectionObject DetectionEfficient Meta-Learning Enabled Lightweight Multiscale Few-Shot Object Detection in Remote Sensing Images
Presently, the task of few-shot object detection (FSOD) in remote sensing images (RSIs) has become a focal point of attention. Numerous few-shot detectors, particularly those based on two-stage detectors, face challenges…
Few-Shot Object DetectionMeta-Learningobject-detectionObject DetectionMultimodal Object Detection in Remote Sensing
Object detection in remote sensing is a crucial computer vision task that has seen significant advancements with deep learning techniques. However, most existing works in this area focus on the use of generic object dete…
Objectobject-detectionObject DetectionSurvey