Deep long-tailed learning a survey
WebAug 22, 2024 · Extensive experiments on three long-tailed classification benchmarks and two deep metric learning benchmarks (person re-identification, in particular) demonstrate the significant improvement. Moreover, the achieved performance are on par with the state-of-the-art on both tasks. WebLarge-scale datasets play a crucial role in deep repre-sentation learning, as well as in many other deep learning based visual tasks. In the real-world, large-scale datasets often exhibit extreme long-tailed distribution [8, 10]. Con-cretely, some identities have sufficient samples, while for other massive identities, only very few samples are ...
Deep long-tailed learning a survey
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WebJun 13, 2024 · It is demonstrated, theoretically and empirically, that class-imbalanced learning can significantly benefit in both semi- supervised and self-supervised manners and the need to rethink the usage of imbalanced labels in realistic long-tailed tasks is highlighted. Real-world data often exhibits long-tailed distributions with heavy class …
WebJul 1, 2024 · The heavy reliance on data is one of the major reasons that currently limit the development of deep learning. Data quality directly dominates the effect of deep learning models, and the long-tailed distribution is one of the factors affecting data quality. The long-tailed phenomenon is prevalent due to the prevalence of power law in nature. WebJul 27, 2024 · Deep long-tailed learning: A survey. arXiv preprint arXiv:2110.04596, 2024. 2. Learning debiased representation via disentangled feature augmentation. Jan 2024; Jungsoo Lee; Eungyeup Kim;
WebDeep long-tailed learning, one of the most challenging problems in visualrecognition, aims to train well-performing deep models from a large number ofimages that follow a long … WebApr 14, 2024 · Mainstream long-tailed learning methods focus on model structure and representation, while data augmentation has received little attention. ... Hooi, B., Yan, S., …
WebOct 14, 2024 · When deep learning meets long-tailed datasets during training, it will learn a biased model since the head classes dominate the parameter optimization, resulting in …
WebOct 9, 2024 · Deep Long-Tailed Learning: A Survey. Deep long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing deep … poem about philippine literatureWebLarge-scale datasets play a crucial role in deep repre-sentation learning, as well as in many other deep learning based visual tasks. In the real-world, large-scale datasets often … poem about practical researchWebJul 1, 2024 · Download Citation A Survey on Long-Tailed Visual Recognition The heavy reliance on data is one of the major reasons that currently limit the development of deep … poem about personal goalsWebJun 14, 2024 · These methods are sometimes regarded as “Direct” in other surveys because they directly applies the definition of metric learning. The distance function in the embedding space for these approaches is usually fixed as l2 metric: D(p, q) = ‖p − q‖2 = ( n ∑ i = 1(pi − qi)2)1 / 2. For the ease of notation, let’s denote Dfθ(x1, x2 ... poem about overcoming fearWebOct 9, 2024 · Abstract: Deep long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing deep models from a large number of … poem about planting a treeWebIn fact, this scheme leads to a contradiction between the two goals of long-tailed learning, i.e., learning generalizable representations and facilitating learning for tail classes. In this work, we explore knowledge distillation in long-tailed scenarios and propose a novel distillation framework, named Balanced Knowledge Distillation (BKD), to ... poem about police officersWebOct 9, 2024 · Abstract. Deep long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing deep models from a large number of images that follow a long-tailed ... poem about poppies in flanders field