Self-Supervised Person Re-Identification
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Benchmarks
SYSU-30k
Most implemented
A Simple Framework for Contrastive Learning of Visual Representations
Improved Baselines with Momentum Contrastive Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Solving Inefficiency of Self-supervised Representation Learning
Papers
Solving Inefficiency of Self-supervised Representation Learning
Self-supervised learning (especially contrastive learning) has attracted great interest due to its huge potential in learning discriminative representations in an unsupervised manner. Despite the acknowledged successes, …
ClusteringContrastive LearningPerson Re-IdentificationRepresentation Learning+4Bootstrap your own latent: A new approach to self-supervised Learning
We introduce Bootstrap Your Own Latent (BYOL), a new approach to self-supervised image representation learning. BYOL relies on two neural networks, referred to as online and target networks, that interact and learn from …
Image ClassificationLinear evaluationPerson Re-IdentificationRepresentation Learning+4Improved Baselines with Momentum Contrastive Learning
Contrastive unsupervised learning has recently shown encouraging progress, e.g., in Momentum Contrast (MoCo) and SimCLR. In this note, we verify the effectiveness of two of SimCLR's design improvements by implementing th…
Contrastive LearningData AugmentationImage ClassificationPerson Re-Identification+3A Simple Framework for Contrastive Learning of Visual Representations
This paper presents SimCLR: a simple framework for contrastive learning of visual representations. We simplify recently proposed contrastive self-supervised learning algorithms without requiring specialized architectures…
Contrastive LearningImage ClassificationObject RecognitionPerson Re-Identification+4