今天介绍一篇关于行人重识别UDA的方法,“Unsupervised Multi-Source Domain Adaptation for Person Re-Identifification ” 论文地址: https://arxiv.org/pdf/2104.12961.pdfarxiv.org/pdf/2104.12961.pdf Motion 以前UDA的方法,都是从一个标记了数据的域获取信息来适应另一个无标签的域。但是reid发展至今,有...
We address the problem of multi-source unsupervised domain adaptation (MS-UDA) for the purpose of visual recognition. As opposed to single source UDA, MS-UDA deals with multiple labeled source domains and a single unlabeled target domain. Notice that the conventional MS-UDA training is based on...
Cross-view consistent soft multilabel learning :由于re-id旨在匹配不同相机下的同一个目标,不同相机下的无标签图片,特征分布应该是一致的。本文用2-Wasserstein distance对特征分布进行约束。 Reference agent learning: 由于source domain中每个已知标签的样本充当独一无二的参考,因此希望他们彼此具有较高的辨识度。
Unsupervised Multi-source Domain Adaptation Without Access to Source Data (CVPR '21 Oral) Overview This repository is a PyTorch implementation of the paper Unsupervised Multi-source Domain Adaptation Without Access to Source Data published at CVPR 2021. This code is based on the SHOT repository. Dep...
we first review this work on multi-source source-freeunsupervised domain adaptationfollowed by analysis of a new algorithm which we propose by relaxing some of the assumptions of this prior work. More specifically, instead of naively assuming sourcedata distributionas uniform, we try to estimate it...
machine-learningcomputer-visionobject-detectiondomain-adaptationunsupervised-domain-adaptationdomain-adaptive-object-detection UpdatedAug 29, 2024 Python (RA-L 2022) See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation. ...
Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift Ruijia Xu1,†, Ziliang Chen1,†, Wangmeng Zuo2, Junjie Yan3, Liang Lin1,3∗ 1Sun Yat-sen University 2Harbin Institute of Technology 3SenseTime Research xurj3@mail2.sysu.edu.cn, c.ziliang@yahoo.com,...
DAFormer stabilizes training and avoids overfitting to the source domain via the rare class sampling, thing-class ImageNet feature distance, and learning rate warmup. HRDA (Hoyer et al., 2022b) presents a multi-resolution training approach for the UDA in semantic segmentation, combining high-...
Hence, we developed an unsupervised multi-source domain adaptation network (P3-MSDA) for dynamic visual target detection. In this network, a P3 map-... X Song,Y Zeng,L Tong,... - 《Frontiers in Human Neuroscience》 被引量: 0发表: 2021年 Unsupervised domain adaptation: A multi-task learn...
^Munro, J., & Damen, D. (2020). Multi-modal domain adaptation for fine-grained action recognition. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 122-132).http://openaccess.thecvf.com/content_CVPR_2020/papers/Munro_Multi-Modal_Domain_Adaptation_fo...