Unsupervised Person Re-Identification
58 papers with code • 19 benchmarks • 11 datasets
Benchmarks
These leaderboards are used to track progress in Unsupervised Person Re-Identification
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Datasets
Market-1501
DukeMTMC-reID
MSMT17
MARS
DukeMTMC-VideoReID
iLIDS-VID
Most implemented papers
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
michuanhaohao/transreid-ssl
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We first investigate self-supervised learning (SSL) methods with Vision Transformer (ViT) pretrained on unlabelled person images (the LUPerson dataset), and empirically find it significantly surpasses ImageNet supervised pre-training models on ReID tasks.
Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification
yanan-wang-cs/clonedperson
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CVPR 2022
To address this, in this work, an automatic approach is proposed to directly clone the whole outfits from real-world person images to virtual 3D characters, such that any virtual person thus created will appear very similar to its real-world counterpart.
Unsupervised Person Re-identification: Clustering and Fine-tuning
hehefan/Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning
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Progressively, pedestrian clustering and the CNN model are improved simultaneously until algorithm convergence.
Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification
While metric learning is important for Person re-identification (RE-ID), a significant problem in visual surveillance for cross-view pedestrian matching, existing metric models for RE-ID are mostly based on supervised learning that requires quantities of labeled samples in all pairs of camera views for training.
Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns
ahangchen/TFusion
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CVPR 2018
Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly deploying these trained models to a large-scale real-world camera network may lead to poor performance due to underfitting.
Deep Association Learning for Unsupervised Video Person Re-identification
yanbeic/Deep-Association-Learning
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In this work, to address the video person re-id task, we formulate a novel Deep Association Learning (DAL) scheme, the first end-to-end deep learning method using none of the identity labels in model initialisation and training.
Leveraging Virtual and Real Person for Unsupervised Person Re-identification
For training of deep re-ID model, we divide it into three steps: 1) pre-training a coarse re-ID model by using virtual data; 2) collaborative filtering based positive pair mining from the real data; and 3) fine-tuning of the coarse re-ID model by leveraging the mined positive pairs and virtual data.
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
Upon our SSG, we further introduce a clustering-guided semisupervised approach named SSG ++ to conduct the one-shot domain adaption in an open set setting (i. e. the number of independent identities from the target domain is unknown).
Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding
In such a way, DECAMEL jointly learns the feature representation and the unsupervised asymmetric metric.
Unsupervised Person Re-identification by Soft Multilabel Learning
KovenYu/MAR
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CVPR 2019
To overcome this problem, we propose a deep model for the soft multilabel learning for unsupervised RE-ID.
