Incremental Learning in Person Re-Identification

August 20, 2018 · Entered Twilight · 🏛 arXiv.org

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Repo contents: README.md, clr.py, cmc_figures_data, covariance_duke.py, covariance_ensembling.py, covariance_market1501.py, dataset_loader.py, dataset_manager.py, evaluation.py, loss.py, lwf_train_modules, metrics.py, models, random_erasing.py, requirements.txt, resuming.py, samplers.py, train_triplet.py, transforms.py, utils.py

Authors Prajjwal Bhargava arXiv ID 1808.06281 Category cs.CV: Computer Vision Citations 2 Venue arXiv.org Repository https://github.com/prajjwal1/person-reid-incremental ⭐ 16 Last Checked 2 months ago

Abstract

Person Re-Identification is still a challenging task in Computer Vision due to a variety of reasons. On the other side, Incremental Learning is still an issue since deep learning models tend to face the problem of over catastrophic forgetting when trained on subsequent tasks. In this paper, we propose a model that can be used for multiple tasks in Person Re-Identification, provide state-of-the-art results on a variety of tasks and still achieve considerable accuracy subsequently. We evaluated our model on two datasets Market 1501 and Duke MTMC. Extensive experiments show that this method can achieve Incremental Learning in Person ReID efficiently as well as for other tasks in computer vision as well.