Y Zhang, XS Wei, B Zhou, J Wu - … of the AAAI conference on artificial …, 2021 - ojs.aaai.org
In recent years, visual recognition on challenging long-tailed distributions, where classes often exhibit extremely imbalanced frequencies, has made great progress mostly based on …
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 …
In the real world, large-scale datasets for visual recognition typically exhibit a long-tailed distribution, where only a few classes contain adequate samples but the others have (much) …
Long-tailed datasets are very frequently encountered in real-world use cases where few classes or categories (known as majority or head classes) have higher number of data …
Y Xu, YL Li, J Li, C Lu - European Conference on Computer Vision, 2022 - Springer
Long-tailed image recognition presents massive challenges to deep learning systems since the imbalance between majority (head) classes and minority (tail) classes severely skews …
The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions …
B Zhou, Q Cui, XS Wei… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
Our work focuses on tackling the challenging but natural visual recognition task of long- tailed data distribution (ie, a few classes occupy most of the data, while most classes have …
Deep learning algorithms face great challenges with long-tailed data distribution which, however, is quite a common case in real-world scenarios. Previous methods tackle the …
M Li, Y Cheung, Y Lu - … of the IEEE/CVF Conference on …, 2022 - openaccess.thecvf.com
Long-tailed data is still a big challenge for deep neural networks, even though they have achieved great success on balanced data. We observe that vanilla training on long-tailed …