【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...
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...
Source-Free domain adaptive Object Detection (SFOD) is a promising strategy for deploying trained detectors to new, unlabeled domains without accessing source data, addressing significant concerns around data privacy and efficiency. Most SFOD methods leverage a Mean-Teacher (MT) self-training paradigm ...
Domain adaptationKnowledge distillationSemi-supervisedYOLODomain adaptive object detection (DAOD) aims to alleviate transfer performance degradation caused by the ... H Zhou,F Jiang,H Lu - 《Computer Vision & Image Understanding Cviu》 被引量: 0发表: 2023年 Multiscale Domain Adaptive YOLO for Cross...
@inproceedings{vs2023instance, title={Instance relation graph guided source-free domain adaptive object detection}, author={VS, Vibashan and Oza, Poojan and Patel, Vishal M}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={3520--3530}, ...
We are currently working on refactoring all the original code. Please wait for the final version. However, you can run the example code using the instructions below. This is an official code implementation repository forEnhancing Source-Free Domain Adaptive Object Detection with Low-confidence Pseudo...
Table 2: A comparison of results for Waymo →nuScenesdomain shift scenario from the proposed method with that of a recent domain adaptive 3D object detector ST3D [34], statistical normalization (SN) [32], the source-modelperformance, and the oracleperformanceof the object detector. Our proposed...
Unsupervised Domain Adaptation. 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 iss...
Benchmarking robustness in object detection: Autonomous driving when winter is coming. arXiv preprint arXiv:1907.07484, 2019. [55] Luigi Musto and Andrea Zinelli. Semantically adaptive image-to-image translation for domain adaptation of semantic segmentation. In BMVC, 2020. [56] Fei Pan,...
The official implementation of the method of Uncertainty-aware Mean Teacher for Source-free Unsupervised Domain Adaptive Object Detection - deeptibhegde/UncertaintyAwareMeanTeacher