Oriented Object Detector With Gaussian Distribution Cost Label Assignment and Task-Decoupled Head

计算机科学 目标检测 探测器 人工智能 旋转(数学) 计算机视觉 水准点(测量) 高斯分布 高斯过程 模式识别(心理学) 电信 物理 量子力学 大地测量学 地理
作者
Qiangqiang Huang,Ruilin Yao,Xiaoqiang Lu,Jishuai Zhu,Shengwu Xiong,Yaxiong Chen
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:62: 1-16
标识
DOI:10.1109/tgrs.2024.3395440
摘要

Recently, oriented object detection in remote sensing images has garnered significant attention due to its broad range of applications. Early oriented object detection adhered to the established general object detection frameworks, utilizing the label assignment strategy based on the horizontal bounding box annotations or rotation-agnostic cost function. Such strategy may not reflect the large aspect ratio and rotation of arbitrary-oriented objects in remota sensing images and require high parameter-tuning efforts in training process, which will eventually harm the detector performance. Furthermore, the localization quality of oriented object depends on precise rotation angle prediction, exacerbating the inconsistency between classification and regression tasks in oriented object detection. To address these issues, we propose the Gaussian Distribution Cost Optimal Transport Assignment (GCOTA) and Decoupled Layer Attention Angle Head (DLAAH). Specifically, GCOTA utilize Gaussian distribution based cost function for the optimal transport label assignment in training process, alleviating the impact of rotation angle and large aspect ratio in remote sensing images. DLAAH predicts rotation angle independently and incorporates layer attention to obtain the task-specific features based on the shared FPN features, enhancing the angle prediction and improving consistency across different tasks. Based on these proposed components, we present an anchor-free oriented detector, namely Gaussian Distribution and Task-Decoupled head oriented Detector(GTDet) and a a multi-class ship detection dataset in real scenarios (CGWX), which provides a benchmark for fine-grained object recognition in remote sensing images. Comprehensive experiments are conducted on CGWX and several public challenging datasets, including DOTAv1.0, HRSC2016, to demonstrate that our method achieves superior performance on oriented object detection task. The code is available at https://github.com/WUTCM-Lab/GTDet.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
顾矜应助耶耶耶采纳,获得10
1秒前
欢喜依霜完成签到 ,获得积分10
2秒前
2秒前
默苍离倒拔琉璃树完成签到,获得积分10
2秒前
RNAPW发布了新的文献求助10
2秒前
吱吱完成签到,获得积分20
3秒前
123发布了新的文献求助10
6秒前
可乐完成签到 ,获得积分10
6秒前
长安心动明月完成签到,获得积分10
8秒前
666pop完成签到,获得积分10
9秒前
小学僧留下了新的社区评论
10秒前
马铃薯完成签到,获得积分10
13秒前
我是老大应助早点睡觉丶采纳,获得10
14秒前
丘比特应助苹果白凝采纳,获得50
15秒前
18秒前
123完成签到,获得积分10
18秒前
爆米花应助是子子子子枫采纳,获得30
19秒前
gghh完成签到 ,获得积分10
19秒前
19秒前
xyx完成签到,获得积分20
20秒前
xyx发布了新的文献求助10
22秒前
聪明的破茧完成签到,获得积分10
24秒前
sdyswgm发布了新的文献求助10
25秒前
JJ完成签到,获得积分10
27秒前
28秒前
yx_cheng应助科研通管家采纳,获得20
30秒前
天天快乐应助科研通管家采纳,获得10
30秒前
30秒前
云霄雨霁完成签到,获得积分10
30秒前
30秒前
bkagyin应助科研通管家采纳,获得10
30秒前
30秒前
30秒前
CipherSage应助科研通管家采纳,获得10
30秒前
30秒前
33秒前
33秒前
34秒前
35秒前
35秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3975658
求助须知:如何正确求助?哪些是违规求助? 3519986
关于积分的说明 11200481
捐赠科研通 3256410
什么是DOI,文献DOI怎么找? 1798247
邀请新用户注册赠送积分活动 877490
科研通“疑难数据库(出版商)”最低求助积分说明 806376