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Found 5 papers, 2 papers with code
Identity-Seeking Self-Supervised Representation Learning for Generalizable Person Re-identification
To overcome the barriers of data and annotation, we propose to utilize large-scale unsupervised data for training.
Generalizable Person Re-identification
Representation Learning
Generalizable Re-Identification from Videos with Cycle Association
In this paper, we are interested in learning a generalizable person re-identification (re-ID) representation from unlabeled videos.
Domain Generalization
Generalizable Person Re-identification
+1
Reliability-Aware Prediction via Uncertainty Learning for Person Image Retrieval
(3) the data uncertainty and the model uncertainty are jointly learned in a unified network, and they serve as two fundamental criteria for the reliability assessment: if a probe is high-quality (low data uncertainty) and the model is confident in the prediction of the probe (low model uncertainty), the final ranking will be assessed as reliable.
Portrait Interpretation and a Benchmark
Furthermore, we focus on representation learning for portrait interpretation and propose a baseline that reflects our systematic perspective.
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective
If a sample belongs to a tail class, the corresponding feature cloud will have relatively large distribution range, in compensation to its lack of diversity.
