随着人们对数据隐私保护的迫切需要,近年来,无源目标检测(source - free Object Detection, SFOD)作为数据保护检测的一个新兴分支应运而生。由于目标检测任务的复杂性(多区域、多尺度特征和复杂的网络结构)和缺乏源数据的挑战性,简单地将现有的udaclclassification或UDAOD方法应用于SFOD任务并不能得到满意的结果[48,26]...
【CVPR23 无源域适应】Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection 诗和远方 督促我,一个域适应小白的奋斗历程13 人赞同了该文章 目录 收起 UDA方法旨在通过对齐源域和目标域之间检测器模型的特征分布来最小化域差。为了执行特征对齐,UDA方法需要同时访问已标记的源数据和未标记...
Source-free object detectionTransfer learningDomain adaptationThe Journal of Supercomputing - Domain adaptive object detection refers to training a cross-domain object detector through a large number of labeled source domain datasets and unlabeled target......
Source-free domain adaptation (SFDA) is a challenging problem in object detection, where a pre-trained source model is adapted to a new target domain without using any source domain data for privacy and efficiency reasons. Most state-of-the-art SFDA methods for object detection have been ...
论文标题:Refined Pseudo labeling for Source-free Domain Adaptive Object Detection论文作者:Siqi Zhang, Lu Zhang, Zhiyong Liu论文来源:2023 ArXiv论文地址:download 论文代码:download视屏讲解:click 1 介绍领域自适应目标检测(DAOD)假设带标记的源数据和未标记的目标数据都可以用于训练,但这种假设在现实世界中并...
Trinh Le Ba Khanh, Huy-Hung Nguyen, Long Hoang Pham, Duong Nguyen-Ngoc Tran and Jae Wook Jeon Official Pytorch implementation ofDynamic Retraining-Updating Mean Teacher for Source-Free Object Detection, ECCV 2024paper. The overview of our DRU method is presented in the following figure. For mor...
Source-free domain adaptation (SFDA) is a challenging problem in object detection, where a pre-trained source model is adapted to a new target domain without using any source domain data for privacy and efficiency reasons. Most state-of-the-art SFDA methods for object detection have been propos...
Source-free domain adaptation (SFDA) is a challenging problem in object detection, where a pre-trained source model is adapted to a new target domain without using any source domain data for privacy and efficiency reasons. Most state-of-the-art SFDA methods for object detection have been ...
We investigate the problem of source-free domain adaptation for object detection and identify some of the major challenges that need to be addressed. We introduced an Instance Relation Graph (IRG) framework to model the relationship between proposals generated by the region proposal network. We ...
UDA methods have been extensively applied to a broad range of computer vi- sion tasks, including image classification [27], semantic seg- mentation [28], object detection [29], and reinforcement learning [30] to tackle the issue of data distribution shift....