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20152021
most citedUnsupervised Person Re-identification by Soft Multilabel Learning

61 citations · 86 across the 4 of their papers we have counts for

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7 papers · 1 filter

cs.CV2021

Transformer-based Dual Relation Graph for Multi-label Image Recognition

Jiawei Zhao, Ke Yan, Yifan Zhao +3

The simultaneous recognition of multiple objects in one image remains a challenging task, spanning multiple events in the recognition field such as various object scales, inconsist…

cs.CV202121 cited

Discriminator-Free Generative Adversarial Attack

Shaohao Lu, Yuqiao Xian, Ke Yan +5

The Deep Neural Networks are vulnerable toadversarial exam-ples(Figure 1), making the DNNs-based systems collapsed byadding the inconspicuous perturbations to the images. Most of t…

cs.CV2021

Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query

Guanyu Cai, Jun Zhang, Xinyang Jiang +7

Text-based image retrieval has seen considerable progress in recent years. However, the performance of existing methods suffers in real life since the user is likely to provide an…

cs.CV2019

Semi-Supervised Adversarial Monocular Depth Estimation

Rongrong Ji, Ke Li, Yan Wang +6

In this paper, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available. To achieve a high regression accuracy, t…

cs.CV201961 cited

Unsupervised Person Re-identification by Soft Multilabel Learning

Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu +3

Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models,…

cs.CV2018

Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training

Feng Zheng, Cheng Deng, Xing Sun +5

Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other. However, due to the challenging pra…